The present disclosure relates to a computation system, a charging plan creation program, and a discharging plan creation program which create a charging plan or a discharging plan for a secondary battery.
In recent years, electric vehicles (EV) and plug-in hybrid vehicles (PHV) have become popular. These electric vehicles are equipped with a secondary battery as a key device. Appropriate charge and discharge management of the secondary battery is required to reduce degradation of the secondary battery and extend the life of the secondary battery.
Cost management is highly required for commercial vehicles such as delivery vehicles. It is desired to create a charging plan that reduces the degradation of the secondary battery during the nighttime when the electricity fees are low. When creating the charging plan, it is necessary to create an optimal charging plan according to daily changes in the state of charge (SOC) before charging and the time available for charging.
With respect to the creation of a charging plan, control for changing the charging pattern in real time according to the state of internal parameters has been proposed. Such a control is based on the premise of fast charging, and an upper limit current value that is less likely to cause degradation is set (see, for example, Patent Literature (PTL) 1). Moreover, in view of storage degradation and cycle degradation, control for determining the SOC at time of storage during which charging and discharging are not performed has been proposed (see, for example, PTL 2).
In the conventional controls, current control, time control, and SOC control while charging is suspended cannot be optimized at the same time.
The present disclosure has been conceived in view of such circumstances. An object of the present disclosure is to provide a technique for creating a charging plan or a discharging plan that minimizes costs, such as degradation of a secondary battery.
In order to solve the above problem, a computation system according to one aspect of the present disclosure includes: a path finder which (sets a plurality of nodes in a state of charge (SOC) zone that is between a target SOC and a present SOC of a secondary battery provided in an electric moving body, (ii) sets a plurality of nodes in a chargeable time period that is between a charging start time and a charging end time, and (iii) finds a charging path from the present SOC at the charging start time to the target SOC at the charging end time via nodes among the plurality of nodes set in the SOC zone and the chargeable time period, the target SOC being set when the secondary battery is charged; a charging plan creator which creates a charging plan based on the charging path found; a cost assigner which refers to at least one of a storage degradation characteristic, a charge cycle degradation characteristic, or a time-of-use electricity fee table to assign a cost of a degradation amount or an electricity fee to each of paths between the plurality of nodes, the storage degradation characteristic defining a storage degradation rate that is defined by at least one element including at least one of the SOC or a temperature of the secondary battery, the charge cycle degradation characteristic defining a cycle degradation rate at a time of charging that is defined by at least one element including at least one of the SOC or a current rate of charging current of the secondary battery. The path finder finds a charging path that minimizes a total cost of paths between the nodes.
It should be noted that any combination of the above-described structural elements and results of conversion of the representation of the present disclosure between devices, methods, systems, computer programs, etc. are also effective as aspects of the present disclosure.
According to the present disclosure, it is possible to create a charging plan or a discharging plan that minimizes costs such as degradation of a secondary battery.
The business operator (in this description, a delivery company is assumed) owns a plurality of electric vehicles 3 and a plurality of chargers 4, and utilizes electric vehicles 3 for the delivery business. In the present embodiment, each electric vehicle 3 is assumed to be a pure electric vehicle (EV) without an engine.
Each of electric vehicles 3 includes a wireless communication function, and is connectable to network 2 to which computation system 1 is connected. Electric vehicle 3 is capable of transmitting battery data of a secondary battery included in electric vehicle 3 to computation system 1 via network 2. Electric vehicle 3 may transmit the battery data while electric vehicle 3 is parked in the parking lot of the business office or in the garage, or while electric vehicle 3 is traveling.
Network 2 is a general term for communication paths such as the Internet and dedicated lines, and any communication medium or protocol may be used. Examples of the communication medium that can be used include a mobile phone network (cellular network), wireless local area network (LAN), wired LAN, optical fiber network, asymmetric digital subscriber line (ADSL) network, and community antenna television (CATV) network. Examples of the communication protocol that can be used include transmission control protocol (TCP)/internet protocol (IP), user datagram protocol (UDP)/IP, and Ethernet (registered trademark).
It may be that electric vehicle 3 is connected to the server or PC of the business operator via a peer-to-peer (P2P) network to directly transmit the battery data of the secondary battery included in electric vehicle 3 to the server or PC of the business operator. It may also be that the battery data is transferred to the server or PC of the business operator via a recording medium on which the battery data is recorded. Electric vehicle 3 may also transmit the battery data to the server or PC of the business operator via charging adapter 6 (see
Vehicle controller 30 is a vehicle electronic control unit (ECU) that controls the entire electric vehicle 3, and may be configured with, for example, an integrated vehicle control module (VCM). Wireless communicator 36 performs signal processing for wireless connection to network 2 via antenna 36a. Examples of the wireless communication network to which electric vehicle 3 can be wirelessly connected include a mobile phone network (cellular network), wireless LAN, electronic toll collection system (ETC), dedicated short range communications (DSRC), vehicle-to-infrastructure (V2I), and vehicle-to-vehicle (V2V).
First relay RY1 is a contactor disposed between lines connecting power supply system 40 and inverter 35. When the vehicle is traveling, vehicle controller 30 turns first relay RY1 into an ON state (closed state) to electrically connect power supply system 40 and the power system of electric vehicle 3. When the vehicle is not traveling, in principle, vehicle controller 30 turns first relay RY1 into an OFF state (open state) to electrically disconnect power supply system 40 from the power system of electric vehicle 3. Note that other types of switches, such as semiconductor switches, may be used instead of relays.
By connecting electric vehicle 3 to charger 4, battery module 41 in power supply system 40 can be externally charged. In the present embodiment, electric vehicle 3 is connected to charger 4 via charging adapter 6. Charging adapter 6 is attached to, for example, the tip of the terminal of charger 4. When charging adapter 6 is attached to charger 4, the controller in charging adapter 6 establishes a communication channel with the controller in charger 4.
When charging adapter 6 attached to charger 4 and electric vehicle 3 are connected by a charging cable, battery module 41 in electric vehicle 3 can be charged from charger 4. Charging adapter 6 lets the electric power supplied from charger 4 to pass through charging adapter 6 to electric vehicle 3. Charging adapter 6 includes a wireless communication function, and is capable of exchanging data with computation system 1. Charging adapter 6 functions as a gateway that relays communications between electric vehicle 3 and charger 4, between electric vehicle 3 and computation system 1, and between charger 4 and computation system 1.
Charger 4 is connected to commercial power system 5, and charges power supply system 40 in electric vehicle 3. In electric vehicle 3, second relay RY2 is disposed between lines connecting power supply system 40 and charger 4. Note that other types of switches, such as semiconductor switches, may be used instead of relays. Battery manager 42 turns on second relay RY2 directly or via vehicle controller 30 before charging starts, and turns off second relay RY2 after charging ends.
Generally, batteries are charged with alternating current for normal charging and with direct current for fast charging. When charging with AC (for example, single-phase 100/200 V) is performed, an AC/DC converter (not illustrated) disposed between second relay RY2 and power supply system 40 converts the AC power into DC power. When charging with DC, charger 4 generates DC power by full-wave rectifying the AC power supplied from commercial power system 5 and smoothing the rectified DC power with a filter.
Example of the fast charging standards that can be used include CHAdeMO (registered trademark), ChaoJi, GB/T, and combined charging system (Combo). CHAdeMO 2.0 defines the maximum output (specification) as 1000 V×400 A=400 kW. CHAdeMO 3.0 defines the maximum output (specification) as 1500 V×600 A=900 kW. ChaoJi defines the maximum output (specification) as 1500 V×600 A=900 kW. GBIT defines the maximum output (specification) as 750 V×250 A=185 kW. Combo defines the maximum output (specification) as 900 V×400 A=350 kW. CHAdeMO, ChaoJi, and GB/T employ controller area network (CAN) as a communication scheme. Combo employs power line communication (PLC) as a communication scheme.
A charging cable adopting the CAN system also includes a communication line in addition to a power line. When electric vehicle 3 and charging adapter 6 are connected with the charging cable, vehicle controller 30 establishes a communication channel with the controller in charging adapter 6. In addition, in the charging cable adopting the PLC system, a communication signal is superimposed on the power line and transmitted.
Vehicle controller 30 establishes a communication channel with battery manager 42 via an in-vehicle network (for example, CAN or local interconnect network (LIN)). When the communication standard between vehicle controller 30 and the controller in charging adapter 6 is different from the communication standard between vehicle controller 30 and battery manager 42, vehicle controller 30 functions as a gateway.
Although details will be described later, in the present embodiment, computation system 1 includes a function of creating an optimum charging plan (charging schedule). Upon receiving the charging plan from computation system 1, the controller in charging adapter 6 transfers the received charging plan to the controller in charger 4. In such a case, even when the controller in charging adapter 6 receives a command value for the charging current from vehicle controller 30, the controller in charging adapter 6 does not transfer the command value to the controller in charger 4. When the controller in charging adapter 6 receives the upper limit values (limit values) of power, current, and voltage from vehicle controller 30, the controller in charging adapter 6 transfers the upper limit values to the controller in charger 4.
It is preferable that charging adapter 6 is configured with a small housing. In this case, the driver of electric vehicle 3 is able to easily carry charging adapter 6, and is able to attach charging adapter 6 to another charger 4, which is other than chargers 4 provided in the office, for use. For example, charging adapter 6 can be attached to charger 4 provided in public facilities, commercial facilities, gas stations, car dealers, and service areas of highways as charger 4 other than chargers 4 provided in the office, and used. In this case, battery module 41 in electric vehicle 3 can also be charged from charger 4 outside the office based on the charging plan created by computation system 1.
Power supply system 40 provided in electric vehicle 3 includes battery module 41 and battery manager 42. Battery module 41 includes a plurality of cells E1-En connected in series. Battery module 41 may include a plurality of cells connected in series and parallel. Battery module 41 may be configured by combining a plurality of battery modules. Lithium-ion battery cells, nickel-hydrogen battery cells, lead-acid battery cells, and the like can be used for the cells. Hereinafter, in the present description, an example is assumed where lithium-ion battery cells (nominal voltage: 3.6-3.7 V) are used. The number of cells E1-En connected in series is determined according to the driving voltage of motor 34.
Shunt resistor Rs is connected in series with cells E1-En. Shunt resistor Rs functions as a current sensing element. A Hall element may be used instead of shunt resistor Rs. A plurality of temperature sensors T1 and T2 for detecting the temperatures of cells E1-En are disposed in battery module 41. One temperature sensor may be disposed in a battery module, or one temperature sensor may be disposed for each set of a plurality of cells. Thermistors, for example, can be used as temperature sensors T1 and T2.
Battery manager 42 includes voltage measurer 43, temperature measurer 44, current measurer 45, and battery controller 46. Respective nodes of cells E1-En connected in series and voltage measurer 43 are connected by a plurality of voltage lines. Voltage measurer 43 measures the voltage of each of cells E1-En by measuring the voltage between two adjacent voltage lines. Voltage measurer 43 transmits the measured voltage of each of cells E1-En to battery controller 46.
Since voltage measurer 43 has a higher voltage than battery controller 46, voltage measurer 43 and battery controller 46 are connected by a communication line while being insulated from each other. Voltage measurer 43 can be configured with an application specific integrated circuit (ASIC) or a general-purpose analog front-end IC. Voltage measurer 43 includes a multiplexer and an A/D converter. The multiplexer sequentially outputs voltages between two adjacent voltage lines to the A/D converter. The A/D converter converts the analog voltage input from the multiplexer into a digital value.
Temperature measurer 44 includes resistor voltage dividers and an A/D converter. The A/D converter sequentially converts a plurality of analog voltages divided, by temperature sensors T1 and T2 and a plurality of resistor voltage dividers into digital values, and outputs the digital values to battery controller 46. Battery controller 46 estimates the temperatures of cells E1-En based on the digital values. For example, battery controller 46 estimates the temperature of each of cells E1-En based on the value measured by the temperature sensor closest to each cell E1-En.
Current measurer 45 includes a differential amplifier and an A/D converter. The differential amplifier amplifies the voltage across shunt resistor Rs, and outputs the amplified voltage to the A/D converter. The A/D converter converts the analog voltage input from the differential amplifier into a digital value, and outputs the digital value to battery controller 46. Battery controller 46 estimates currents flowing through cells E1-En based on the digital values.
When battery controller 46 includes an A/D converter and an analog input port, it may be that temperature measurer 44 and current measurer 45 output the analog voltages to battery controller 46, and the A/D converter in battery controller 46 converts the analog voltages into digital values.
Battery controller 46 manages the states of cells E1-En based on the voltages, temperatures, and currents of cells E1-En measured by voltage measurer 43, temperature measurer 44, and current measurer 45. Battery controller 46 can be configured with a microcomputer and a non-volatile memory (for example, (electrically erasable programmable read-only memory (EEPROM) or flash memory). Battery controller 46 estimates the SOC and state of health (SOH) of each of cells E1-En.
Battery controller 46 estimates the SOC by combining an open circuit voltage (OCV) method and a current integration method. The OCV method is a method of estimating the SOC based on the OCV of each cell E1-En measured by voltage measurer 43 and the SOC-OCV curves of cells E1-En. The SOC-OCV curves of cells E1-En are created in advance based on characteristic tests performed by the battery manufacturer and recorded in the internal memory of the microcomputer at the time of shipment.
The current integration method is a method of estimating the SOC based on the OCV at the start of charging and discharging of cells E1-En and the integrated value of the current measured by current measurer 45. In the current integration method, the measurement errors of current measurer 45 are accumulated more as the length of the charging and discharging time periods increase. Accordingly, it is preferable to correct the SOC estimated by the current integration method, using the SOC estimated by the OCV method.
The SOH is defined by the ratio of the present full charge capacity (FCC) to the initial FCC, and the lower the value (closer to 0%), the more advanced the degradation. The SOH may be obtained by capacity measurement by complete charging and discharging, or may be obtained by adding up the storage degradation and cycle degradation.
The SOH can also be estimated based on the correlation with the internal resistance of the cell. The internal resistance can be estimated by dividing the voltage drop that occurs when a given current is applied to the cell for a given period of time, by the current value. The internal resistance decreases as the temperature rises, and the internal resistance increases as the SOH decreases.
Battery controller 46 transmits the voltages, temperatures, currents, SOCs and SOHs of cells E1-En to vehicle controller 30 via the in-vehicle network. Vehicle controller 30 transmits battery data including the present SOCs, SOHs, and temperatures of cells E1-En to computation system 1.
Storage 12 includes storage degradation rate characteristic map 121, charge cycle degradation rate characteristic map 122, discharge cycle degradation rate characteristic map 123, and time-of-use electricity fee table 124. Storage 12 includes a non-volatile recording medium, such as solid state drive (SSD) and hard disk drive (HDD), and records various programs and data.
Storage degradation rate characteristic map 121, charge cycle degradation rate characteristic map 122, and discharge cycle degradation rate characteristic map 123 are obtained by mapping the storage degradation rate characteristics, the charge cycle degradation rate characteristics, and the discharge cycle degradation rate characteristics of the secondary battery provided in electric vehicle 3. The storage degradation rate characteristics, the charge cycle degradation rate characteristics, and the discharge cycle degradation rate characteristics of secondary batteries are derived in advance for each secondary battery product through experiments and simulations performed by battery manufacturers. Note that data derived by other evaluation organizations may also be used.
Storage degradation is degradation that progresses over time in accordance with the temperature and the SOC of the secondary battery at each time point. The storage degradation progresses over time regardless of whether charging or discharging is being performed. Storage degradation is caused mainly by the formation of a film (solid electrolyte interphase (SEI) film) on the negative electrode. Storage degradation depends on the SOC and temperature at each time point. Generally, the storage degradation rate increases as the SOC at each time point increases or the temperature at each time point increases.
Cycle degradation is degradation that progresses as the number of times charging and discharging are performed increases. Cycle degradation is mainly caused by cracking or peeling due to expansion or contraction of the active material. Cycle degradation depends on the current rate, the SOC range used, and the temperature. Generally, the cycle degradation rate increases with an increase in the current rate, the SOC range used, and the temperature.
The cycle degradation characteristics are also influenced by temperature, although not as much as the influence by the current rate. Accordingly, in order to increase the estimation accuracy of the cycle degradation rate, it is preferable to prepare cycle degradation characteristics that define the relationship between the SOC use range and the cycle degradation rate for respective two-dimensional combinations of current rates and temperatures. On the other hand, when generating a simple cycle degradation rate characteristic map, it is only necessary to prepare cycle degradation rate characteristics for each of a plurality of current rates while assuming the temperature as room temperature.
The storage degradation rate characteristics, the charge cycle degradation rate characteristics, and the discharge cycle degradation rate characteristics may be defined by functions instead of maps.
Referring back to
Electric power companies in Japan offer a variety of fee plans. Examples of such plans provided include: (a) a plan that sets fees according to the amount of use regardless of the time of day or day of the week; (b) a plan that sets low fees for the time slot from 1:00a.m. to 9:00a.m.; (c) a plan that sets low fees for the time slot from 9:00p.m. to 5:00a.m. the following morning; (d) a plan that sets low fees for the time slot from 9:00p.m. to 9:00a.m. the following morning; (e) a plan that sets low fees for the time slot from 11:00p.m. to 7:00a.m. the following morning; (f) a plan that sets low fees for the time slot from 10:00p.m. to 8:00a.m. the following morning; (g) a plan that sets low fees for Saturdays an d Sundays; (h) a plan for the summer season divided into three time slots with relatively high fees during the peak hours (1:00p.m. to 4:00p.m.) and low fees during the night time (from 11:00p.m. to 7:00a.m. the following morning); and (i) a plan that sets detailed fees by “season” and “time slot”, and sets low fees for the time slot from 11:00p.m. to 7:00a.m. the following morning.
In the case of a large business operator, such as the delivery business, according to the present embodiment, it is also possible to set a more detailed and customized fee plan through a separate contract between the business operator and the electric power company.
Operator 13 is a user interface such as a keyboard, a mouse, and a touch panel, and receives an operation of the user of computation system 1. Display 14 includes a display such as a liquid crystal display or an organic electro-luminescent (EL) display, and displays an image generated by processor 11. Communicator 15 performs communication processing for communicating with charging adapter 6, electric vehicle 3, or charger 4 directly or via network 2.
Input information obtainer 111 obtains the target SOC, charging start time, and charging end time for charging battery module 41 provided in electric vehicle 3, which are input from operator 13. The time period from the charging start time to the charging end time is the time period available for charging.
Battery data obtainer 112 obtains battery data of battery module 41 from vehicle controller 30 of electric vehicle 3 via communicator 15. The battery data includes at least the present SOCs of cells E1-En included in battery module 41. The battery data may also include the present SOHs and temperatures of cells E1-En.
Path finder 113 sets a plurality of nodes at a predetermined interval in the SOC zone that is between the obtained target SOC and present SOC. For example, the nodes are set in increments of 0.5%. The nodes may be set in different increments such as 1%, 5%, or 10%.
Path finder 113 sets a plurality of nodes at a predetermined interval in the chargeable time period that is between the obtained charging start time and the obtained charging end time. For example, nodes are set in increments of 30 minutes. The nodes may be set in different increments, such as 3 minutes, 5 minutes, 10 minutes, or 15 minutes.
Path finder 113 sets paths between the nodes set in a matrix pattern. Cost assigner 114 refers to storage degradation rate characteristic map 121 and charge cycle degradation rate characteristic map 122 to assign degradation costs to paths between nodes. Path finder 113 finds the charging path that minimizes the total degradation cost of paths between nodes. Charging plan creator 115 creates a charging plan based on the found charging path. Charging plan outputter 116 transmits the created charging plan to charger 4 via charging adapter 6. Specific examples will be described below.
As illustrated in
When the cell temperature is 40° or less, the temperature has little effect on the storage degradation rate, so that cost assigner 114 is capable of assuming that the temperature is room temperature. In that case, cost assigner 114 obtains the storage degradation rate between nodes in the horizontal direction based on the room temperature and the SOC. Cost assigner 114 multiplies the storage degradation rate between nodes in the horizontal direction by units of time (ΔT) to calculate the degradation amount between nodes in the horizontal direction.
Note that cost assigner 114 may assume that the present cell temperature obtained by battery data obtainer 112 continues till the charging end time. In that case, cost assigner 114 obtains the storage degradation rate between nodes in the horizontal direction based on the obtained temperature and SOC. Cost assigner 114 multiplies the storage degradation rate between nodes in the horizontal direction by units of time (ΔT) to calculate the degradation amount between nodes in the horizontal direction.
It may also be that cost assigner 114 obtains weather forecast information for the area where charger 4 is provided from a weather forecast server (not illustrated), and estimates the temperatures between nodes in the horizontal direction from the charging start time to the charging end time. In that case, cost assigner 114 obtains the storage degradation rate between nodes in the horizontal direction based on the estimated temperatures and SOCs between the nodes in the horizontal direction. Cost assigner 114 multiplies the storage degradation rate between nodes in the horizontal direction by units of time (ΔT) to calculate the degradation amount between nodes in the horizontal direction.
On the other hand, during charging, both of the charge cycle degradation and the storage degradation progress. As illustrated in
Although not illustrated in
Cost assigner 114 refers to charge cycle degradation rate characteristic map 122 based on the SOC range and the current rate for each path between nodes in the upper right direction to identify the charge cycle degradation rate. Cost assigner 114 refers to storage degradation rate characteristic map 121 based on the SOC and the temperature to identify the storage degradation rate. For the SOC used to identify the storage degradation rate, for example, the average value of the upper limit value and the lower limit value of the SOC range may be used.
Cost assigner 114 calculates, for each path between nodes in the upper right direction, the charge cycle degradation amount of the path between nodes in the upper right direction by multiplying the identified charge cycle degradation rate by the current amount (Ah) corresponding to the unit of SOC (ΔSOC). Cost assigner 114 multiplies the identified storage degradation rate by units of time (ΔT) for each path between nodes in the upper right direction to calculate the storage degradation amount of the path between nodes in the upper right direction. Cost assigner 114 adds up the calculated charge cycle degradation amount and storage degradation amount for each path between nodes in the upper right direction to calculate the final degradation amount.
In practice, not all paths between nodes can be passed as charging paths, and there is limitation by current or time.
The upper limit values of charging power and charging current are defined for each charger 4 in accordance with the specification of charger 4. Accordingly, it is not possible to perform charging exceeding the upper limit value of the charging current of charger 4. Similarly, the upper limit values of charging power and charging current of each electric vehicle 3 is defined in accordance with the specification of electric vehicle 3. Accordingly, it is not possible to perform charging exceeding the upper limit value of the charging current of electric vehicle 3.
Computation system 1 holds, in an upper limit value table (not illustrated) in storage 12, the upper limit values of charging power and charging current for each charger 4 and the upper limit values of charging power and charging current for each electric vehicle 3. The upper limit values of the charging power and charging current of charger 4 and the upper limit values of the charging power and charging current of electric vehicle 3 may be input by the user via operator 13, or may be obtained from charger 4 or electric vehicle 3 when computation system 1 performs communication with charger 4 or electric vehicle 3 for the first time.
Among the paths between nodes calculated in
In the example illustrated in
Path finder 113 finds the charging path that minimizes the total degradation amount of paths between nodes. Specifically, path finder 113 calculates the total storage degradation amount and the total charge cycle degradation amount of each charging path based on (formula 1) and (formula 2) below. Path finder 113 adds up the total storage degradation amount and the total charge cycle degradation amount to calculate the total degradation amount of each charging path. Path finder 113 selects the charging path that minimizes the total degradation amount.
Total storage degradation amount=≈(Σ(ΔT*Ks{circumflex over ( )}2)) (Formula 1)
Storage degradation rate Ks [%/√h]=storage degradation map (SOC [%], temperature [° C.])
Total charge cycle degradation amount=√(Σ(ΔΔh*Kc{circumflex over ( )}2)) (Formula 2)
Charge cycle degradation rate Kc[%/√Ah]=Charge cycle degradation map (SOC [1%], current rate [C])
Path finder 113 is capable of finding the charging path that minimizes the total degradation amount of paths between nodes using an existing path finding algorithm. For example, Dijkstra's algorithm can be used as a path finding algorithm. Path finding algorithms are commonly used in car navigation systems.
Path finder 113 selects the node with the shortest distance from among the nodes with distances set to infinity, and determines the distance. In the example illustrated in
Next, path finder 113 selects the node with the shortest distance from among the nodes with distances set to infinity, and determines the distance. In the example illustrated in
Next, path finder 113 selects the node with the shortest distance from among the nodes with distances set to infinity, and determines the distance. In the example illustrated in
Next, path finder 113 selects the node with the shortest distance from among the nodes with distances set to infinity, and determines the distance. In the example illustrated in
When path finder 113 finds the charging path that minimizes the degradation amount, charging plan creator 115 converts the found charging path into a charging plan defined by the charging start time and the current value for each unit of time. Charging plan outputter 116 transmits the charging plan created by charging plan creator 115 to charging adapter 6, electric vehicle 3, or charger 4 via communicator 15.
For example, the data format of the charging plan includes the charging start time [s] and the target charging amount [Ah], and defines a plurality of data slots for storing the current values for respective units of time section (for example, every 3 minutes).
Computation system 1 may create a plan for adjusting the temperature in power supply system 40 when battery module 41 in electric vehicle 3 is charged from charger 4. In that case, the temperature adjustment plan is transmitted from computation system 1 to battery manager 42 in electric vehicle 3 directly or via charging adapter 6. For example, the data format of the temperature adjustment plan defines a plurality of data slots for storing target values of temperature for each unit of time (for example, every 3 minutes). Upon receiving the temperature adjustment plan, battery manager 42 adjusts the temperature in battery module 41 according to the temperature adjustment plan. For example, battery manager 42 controls the output of a fan, cooler, or heater (not illustrated) to adjust the temperature in battery module 41.
In the examples illustrated in
The example illustrated in
The example illustrated in
When there are variations between two cells E1 and E2 connected in series, the charging path that minimizes the degradation amount of cell E1 may differ from the charging path that minimizes the degradation amount of cell E2. Accordingly, it is necessary to set an index for determining the charging path for the entire series-connected cells.
A first index is an index that aims at minimizing the degradation amount of the entire cells connected in series. Path finder 113 finds the charging path that minimizes the degradation amount of the cell with a lowest SOH among the cells connected in series. Charging based on such a charging path puts the least load on the cell with a lowest SOH. In a plurality of cells connected in series, the cell with a lowest SOH become bottleneck, and the life of the cell with the lowest SOH determines the life of the entire cells. Use of the first index extends the life of the entire battery module 41.
A second index is an index that aims at minimizing variations in SOH between cells connected in series. Path finder 113 finds the charging path that minimizes the difference in the degradation amount between cells connected in series. Specifically, path finder 113 sets the difference value of the degradation amount (the sum of the differences of the connected cells) as a cost to each path (movement in the horizontal direction and tipper right direction in the case of charging), to find the charging path that minimizes the difference value of the degradation amount. Charging based on such a charging path reduces variations in SOH between cells connected in series. Variations in SOH between cells connected in series lead to a reduction in available capacity and life of the entire cells. On the other hand, the charging path determined based on the second index reduces variations in SOH, contributing to an increase in available capacity and life. In particular, variations in SOH between cells are likely to occur in power supply system 40 which does not include a cell balancing circuit (an equalization circuit).
A third index is an index that aims at preventing reduction of the travelable distance on the next day. Path finder 113 finds the charging path that minimizes the degradation amount of the cell with a lowest actual capacity among the cells connected in series. The actual capacity of a cell (that is, the capacity that can actually be discharged) is defined by SOC×SOH. In charging based on such a charging path, the cell with a lowest actual capacity is reliably charged to the target SOC. The available capacity of the entire cells connected in series depends on the capacity of the cell with a lowest actual capacity. On the other hand, in the charging path determined based on the third index, the cell with the lowest actual capacity is reliably charged to the target SOC. Hence, it is possible to prevent reduction of the available capacity of the entire cells connected in series.
For example, when the first index is set to path finder 113, path finder 113 finds the charging path that minimizes the degradation amount of cell E2. When the third index is set to path finder 113, too, path finder 113 finds the charging path that minimizes the degradation amount of cell E2.
In the examples illustrated in
In the case of a country or region where electricity is traded on the market, such as Pennsylvania New Jersey Maryland (PJM) in the United States, cost assigner 114 obtains the most recent market price for the time slot for charging, and assigns market prices to paths between nodes.
Path finder 113 finds the charging path that minimizes the total fee cost of paths between nodes. Charging plan creator 115 creates a charging plan based on the found charging path. Charging plan outputter 116 transmits the created charging plan to charger 4 directly or via charging adapter 6.
When input information obtainer 111 obtains the index selected by the user input via operator 13, input information obtainer 111 sets the selected index to path finder 113 (S10). The user is able to switch between the four indexes as appropriate. Alternatively, it may be that processor 11 includes an index switcher (not illustrated), and the index switcher switches between the indexes according to a predetermined rule. For example, the index switcher selects index (c) when the SOH of the entire battery module 41 is higher than a first set value, and switches from index (c) to index (a) when the SOH becomes lower than the first set value. Moreover, for example, in a state where the magnitude of difference in SOH between cells E1-En in battery module 41 is less than a second set value, the index switcher selects index (c), and when the magnitude of the variations becomes greater than the second set value, the index switcher switches index (c) to index (b).
Input information obtainer 111 obtains the target SOC at the time of charging of battery module 41 provided in electric vehicle 3, charging start time, and charging end time which are input from operator 13 (S11). Battery data obtainer 112 obtains battery data (including the present SOCs) of cells E1-En included in battery module 41 from vehicle controller 30 of electric vehicle 3 via communicator 15 (S12).
Path finder 113 sets a plurality of nodes at a predetermined interval in the SOC zone that is between the obtained target SOC and present SOC (S13). Path finder 113 sets a plurality of nodes at a predetermined interval in the chargeable time period that is between the obtained charging start time and the charging end time (S14).
Path finder 113 sets paths between the nodes set in a matrix pattern. Cost assigner 114 invalidates paths between nodes that do not satisfy the current limitation and time limitation (S15). Cost assigner 114 refers to at least one of storage degradation rate characteristic map 121, charge cycle degradation rate characteristic map 122, or time-of-use electricity fee table 124 to assign costs to paths between nodes (S16).
Path finder 113 applies a path finding algorithm to find the charging path that minimizes the cost that is in accordance with the set index (S17). Charging plan creator 115 creates a charging plan based on the found charging path (S18). Charging plan outputter 116 transmits the created charging plan to charger 4 directly or via charging adapter 6 (S19).
In configuration example 2, in addition to input information obtainer 111, battery data obtainer 112, path finder 113, cost assigner 114, charging plan creator 115, and charging plan outputter 116, processor 11 further includes delivery plan creator 117, power consumption predicter 118, and SOC use range identifier 119.
Delivery plan creator 117 creates a delivery plan for the next day for each electric vehicle 3 owned by the delivery company based on order information from an order management system (not illustrated). The delivery plan also includes a delivery route. Based on the delivery route included in the delivery plan, power consumption predicter 118 calculates the travel distance of electric vehicle 3 required for delivery on the next day. Power consumption predicter 118 calculates the power consumption required to travel the calculated distance as a predicted value of the power consumption for the next day.
SOC use range identifier 119 derives a plurality of candidates for the use range of SOC of battery module 41 for the next day based on the predicted power consumption for the next day. For example, when the predicted power consumption for the next (lay is equivalent to 50% of the depth of discharge (DOD) of battery module 41, SOC use range identifier 119 derives 100-50%, 90-40%, 80-30%, 70-20%, 60-10%, and 50-0% as a plurality of candidates for the SOC use range. In this example, candidates are derived in increments of 10%, but candidates may be derived in other increments.
Path finder 113 sets, for each of the candidates for the SOC use range, a plurality of nodes at a predetermined interval in the SOC use range. Path finder 113 sets a plurality of nodes at a predetermined interval in the delivery time period that is between the delivery start time and the delivery end time based on the delivery plan for the next day. Path finder 113 sets paths between the nodes set in a matrix pattern. Cost assigner 114 refers to storage degradation rate characteristic map 121 and discharge cycle degradation rate characteristic map 123 to assign degradation costs to paths between nodes.
Path finder 113 finds, for each of the plurality of candidates for the SOC use range, the discharging path that minimizes the total degradation cost of paths between nodes. Path finder 113 identifies the SOC use range of the discharging path with the lowest minimum total degradation cost among the discharging paths which minimizes the total degradation costs for the plurality of candidates for the SOC use range. Path finder 113 sets the upper limit SOC of the identified SOC use range to the target SOC at the time of charging.
The method of assigning the degradation costs to paths between nodes is the same as that for finding a charging path described above, except that the relationship is inverse.
SOC use range identifier 119 derives a plurality of candidates for the SOC use range of battery module 41 for the next day based on the predicted power consumption for the next day (S22). For each of the candidates for the SOC use range, path finder 113 sets a plurality of nodes at a predetermined interval in the SOC zone between the upper limit SOC and the lower limit SOC of the SOC use range (S23). Path finder 113 sets a plurality of nodes at a predetermined interval in the delivery time period between the delivery start time and the delivery end time (S24).
Path finder 113 sets paths between the nodes set in a matrix pattern. Cost assigner 114 invalidates paths between nodes that do not satisfy the current limitation and time limitation (S25). Cost assigner 114 refers to storage degradation rate characteristic map 121 and discharge cycle degradation rate characteristic map 123 to assign degradation costs to paths between nodes (S26).
Path finder 113 applies a path finding algorithm to find the discharging path that minimizes the degradation cost that is in accordance with the set index (S27). In configuration example 2, the index is selected from the following three indexes: (a) minimization of the degradation amount of the cell with a lowest SOH among the cells connected in series; (b) minimization of the difference in the degradation amount between the cells connected in series; and (c) minimization of the degradation amount of the cell with a lowest actual capacity among the cells connected in series.
Path finder 113 identifies the SOC use range of the discharging path with the lowest minimum degradation cost among the discharging paths that minimizes degradation costs for the plurality of candidates for the SOC use range (S28). Path finder 113 sets the upper limit SOC of the identified SOC use range to the target SOC at the time of charging (S29).
In the flowchart illustrated in
Moreover, the SOC use range may be identified by the following process. For each of a plurality (i) of candidates for the SOC use range, path finder 113 applies the predicted discharge pattern to calculate a total degradation amount [i] of the discharging path. For example, for each of candidates for the SOC use range of 100-50%, 90-40%, 80-30%, 70-20%, 60-10%, and 50-0%, path finder 113 calculates a total degradation amount [i] of the discharging path when applying the discharge pattern corresponding to the travel pattern predicted based on the delivery plan. Path finder 113 calculates, for each of the plurality (of candidates for the SOC use range, a total degradation amount [i] of the charging path that minimizes the degradation cost from the present SOC to the upper limit SOC of the SOC use range. For each of the plurality (i) of candidates for the SOC use range, path finder 113 adds up the total degradation amount [i] of the discharging path and the total degradation amount [i] of the charging path. Path finder 113 identifies the SOC use range with a minimum total degradation amount [i]. In this case, there is no need to find a new charging path, and a charging plan is created based on the charging path with the minimum degradation cost calculated above.
Path finder 113 identifies the SOC range of the discharging path with the lowest minimum degradation cost among the discharging paths with the minimum degradation costs for the plurality of candidates for the SOC use range (S28). Discharging plan creator 1110 creates a discharging plan based on the discharging path with the minimum degradation cost of the identified SOC use range (S210). Specifically, discharging plan creator 1110 converts the identified discharging path into a discharging plan defined by the travel start time (discharging start time) and the current value for each unit of time section.
For example, the data format of the discharging plan includes the travel start time [s] and the predicted power consumption [Ah], and defines a plurality of data slots for storing the current values for respective units of time section. Note that discharging plan creator 1110 may convert the current value for each unit of time section into the speed of electric vehicle 3, and store the recommended speed of electric vehicle 3 for each unit of time section in a plurality of data slots.
Discharging plan outputter 1111 transmits the created discharging plan to electric vehicle 3 directly or via charging adapter 6 (S211).
Upon receiving the discharging plan, vehicle controller 30 in electric vehicle 3 displays the recommended speed for each time slot on the in-vehicle display (for example, the display of the car navigation system, or the meter display). When electric vehicle 3 is an automatic driving vehicle, electric vehicle 3 travels at a speed that is as close as possible to the recommended speed for each time slot within the range of safety standards.
The process in the flowchart illustrated in
Path finder 113 sets a plurality of nodes in the SOC use range determined by SOC use range identifier 119, and sets a plurality of nodes in the travelable time period (dischargeable time period) that is between the travel start time (discharging start time) and the travel end time (discharging end time). Cost assigner 114 refers to storage degradation rate characteristic map 121 and discharge cycle degradation rate characteristic map 123 to assign degradation costs to paths between nodes. Path finder 113 finds the discharging path that minimizes the total degradation cost of paths between nodes among discharging paths from the upper limit SOC of the SOC use range at the travel start time to the lower limit SOC of the SOC use range at the travel end time via a plurality of nodes.
As described above, according to the present embodiment, it is possible to create a charging plan or a discharging plan that minimizes costs, such as degradation of the secondary battery. For charging electric vehicle 3 used for delivery business, etc., it is desirable to create a charging plan that minimizes the degradation amount of the secondary battery during the nighttime when the electricity fees are low. The SOC at the start of charging and the chargeable time period available for charging change daily. It is necessary to create an optimum charging plan according to such changes in the SOC at the charting start time and chargeable time period.
In the present embodiment, charging from the present SOC to the target SOC is considered using a path problem. In other words, it is possible to create the optimum charging plan by setting the degradation amount to the passage cost of each path with reference to storage degradation rate characteristic map 121 and charge cycle degradation rate characteristic map 122, and finding the path which minimizes the degradation amount.
With this method, it is possible find the charging pattern with the minimum degradation amount within a specified time period (chargeable time period), and it is possible to collectively perform optimization control on the three elements of current control, time control, and storage SOC. Conventionally, it was not possible to simultaneously obtain the determination of the three elements of current control, time control, and storage SOC with a single mechanism.
Moreover, in the present embodiment, the battery data (SOC, SOH) of cells E1-En is input, so that the amount of degradation of battery module 41 as a whole can be minimized. It is also possible to reduce an increase in the SOH difference between cells E1-En. These control modes can be easily switched by switching the cost index for the paths depending on the intended use.
The present disclosure has been described above based on the embodiment. The embodiment has been given by way of illustration. It will be understood by those skilled in the art that various modifications may be made to combinations of the structural elements and processes, and all such modifications are also intended to fall within the scope of the present disclosure.
In the embodiment described above, four indexes are given as examples. In this regard, an index that aims at both reduction of the cell degradation and saving of electricity fees may be provided. For example, path finder 113 calculates the degradation amount cost and electricity fee cost for each selectable charging path, performs a weighted addition or weighted average on the costs to calculate the total cost, and identifies the charging path with the minimum total cost.
In the embodiment, the example has been described where a charging plan is transmitted to charger 4 via charging adapter 6 from computation system 1. In this regard, charging adapter 6 is not essential, and can be omitted. In that case, the charging plan is transmitted to charger 4 from computation system 1 directly or via electric vehicle 3.
In addition, the index that aims at minimizing electricity fees is not essential, and can be omitted. In that case, time-of-use electricity fee table 124 can be omitted.
In the embodiment, the example has been described where a charging plan or a discharging plan for battery module 41 provided in electric vehicle 3 is created. In this regard, electric vehicle 3 may be a two-wheel electric motorcycle (electric scooter) or an electric bicycle. Examples of electric vehicle 3 include low-speed electric vehicle 3, such as a golf cart and a land car used in shopping malls, entertainment facilities, and the like. Moreover, the object in which battery module 41 is provided is not limited to electric vehicle 3. For example, electric moving bodies, such as electric ships, railroad vehicles, and multicopters (drones), are also included.
The embodiment may be identified by the following items.
[Item 1] A computation system (1) includes: a path finder (113) which (i) sets a plurality of nodes in a state of charge (SOC) zone that is between a target SOC and a present SOC of a secondary battery (41) provided in an electric moving body (3), (ii) sets a plurality of nodes in a chargeable time period that is between a charging start time and a charging end time, and (iii) finds a charging path from the present SOC at the charging start time to the target SOC at the charging end time via nodes among the plurality of nodes set in the SOC zone and the chargeable time period, the target SOC being set when the secondary battery (41) is charged; a charging plan creator (115) which creates a charging plan based on the charging path found; a cost assigner (114) which refers to at least one of a storage degradation characteristic (121), a charge cycle degradation characteristic (122), or a time-of-use electricity fee table (124) to assign a cost of a degradation amount or an electricity fee to each of paths between the plurality of nodes, the storage degradation characteristic (121) being defined by at least one element including at least one of the SOC or a temperature of the secondary battery (41), the charge cycle degradation characteristic (122) defining a cycle degradation rate at a time of charging that is defined by at least one element including at least one of the SOC or a current rate of charging current of the secondary battery (41). The path finder (113) finds a charging path that minimizes a total cost of paths between the nodes.
With this, it is possible to create a charging plan that minimizes charging cost.
[Item 2] In the computation system (1) according to item 1, the charging plan creator (115) creates a charging plan including the charging start time and a current value in each of sections of time.
With this, the current supplied from the charger (4) to the secondary battery (41) provided in the electric moving body (3) can be optimally controlled.
[Item 3] In the computation system (1) according to item 1 or item 2, the cost assigner (114) invalidates a path with a current rate that exceeds an upper limit value of the charging current among the paths between the plurality of nodes, the current rate being required for passage of each of the paths.
With this, it is possible to prevent an impractical charging plan from being created.
[Item 4] In the computation system (1) according to any one of item 1 to item 3, the secondary battery (41) includes a plurality of cells (E1-En) connected in series, and the path finder (113) finds a charging path that minimizes a degradation amount of a cell with a lowest state of health (SOH) among the plurality of cells (E1-En).
With this, it is possible to create a charging plan that minimizes the degradation amount of the entire cells (E1-En).
[Item 5] In the computation system (1) according to any one of item 1 to item 3, the secondary battery (41) includes a plurality of cells (E1-En) connected in series, and the path finder (113) finds a charging path that minimizes a difference in a degradation amount between the plurality of cells (E1-En).
With this, it is possible to create a charging plan that leads to reduction in variations in the degradation amount between the cells (E1-En).
[Item 6] In the computation system (1) according to any one of item 1 to item 3, the secondary battery (41) includes a plurality of cells (E1-En) connected in series, and the path finder (113) finds a charging path that minimizes a degradation amount of a cell with a lowest actual capacity among the plurality of cells (E1-En).
With this, it is possible to create a charging plan that can avoid reduction of the travelable distance of the electric vehicle (3).
[Item 7] In the computation system (1) according to any one of item 1 to item 3, the path finder (113) finds a charging path that minimizes a total electricity fee of the paths between the nodes.
With this, it is possible to create a charging plan that minimizes the electricity fees.
[Item 8] In the computation system (1) according to any one of item 1 to item 7, the path finder (113) is capable of switching an index for determining a cost of a charging path to be minimized.
With this, flexible control can be performed according to the situation.
[Item 9] The computation system (1) according to any one of item 1 to item 8, further includes a SOC use range identifier (19) which derives a plurality of candidates for a SOC use range of the secondary battery (41) based on power consumption predicted to be required for a next use of the electric moving body (3). For each of the plurality of candidates for the SOC use range derived, the path finder (113) sets a plurality of nodes in the SOC use range, and sets a plurality of nodes in a use time period that is between a next use start time and a next use end time of the electric moving body (3), the cost assigner (114) refers to the storage degradation characteristic (121) and a discharge cycle degradation characteristic (123) to assign a degradation cost to each of paths between nodes among the plurality of nodes set in the SOC use range and the use time period, the discharge cycle degradation characteristic (123) defining a cycle degradation rate at a time of discharging that is defined by at least one element including at least one of the SOC or a current rate of discharging current of the secondary battery (41), and the path finder (113) (i) finds, for each of the plurality of candidates for the SOC use range, a discharging path that minimizes a total degradation cost of the paths between the nodes, (ii) identifies a SOC use range of a discharging path with a lowest total degradation cost among the discharging paths each of which minimizes the total degradation cost, and (iii) sets, to the target SOC, an upper limit value of the SOC use range identified.
With this, the target SOC at the time of charging can be automatically determined.
[Item 10] The computation system (1) according to any one of item 1 to item 8, further includes a SOC use range identifier (119) which derives a plurality of candidates for a SOC use range of the secondary battery (41) based on power consumption predicted to be required for a next use of the electric moving body (3). The path finder (113) (i) calculates a degradation amount of a discharging path based on a predicted discharging pattern for each of the plurality of candidates for the SOC use range derived, (ii) calculates a degradation amount of a charging path with a minimum degradation cost from a present SOC to an upper limit SOC for each of the plurality of candidates for the SOC use range, (iii) determines a SOC use range which minimizes a sum of the degradation amount of the discharging path and the degradation amount of the charging path, and (v) sets, to the target SOC, an upper limit value of the SOC use range determined.
With this, the target SOC at the time of charging can be automatically determined.
[Item 11] A charging plan creation program for causing a computer to perform: setting a plurality of nodes in a state of charge (SOC) zone that is between a target SOC and a present SOC of a secondary battery (41) provided in an electric moving body (3), and setting a plurality of nodes in a chargeable time period that is between a charging start time and a charging end time, the target SOC being set when the secondary battery (41) is charged; referring to at least one of a storage degradation characteristic (121), a charge cycle degradation characteristic (122), or a time-of-use electricity fee table (124) to assign a cost of a degradation amount or an electricity fee to each of paths between the plurality of nodes set in the SOC zone and the chargeable time period, the storage degradation characteristic (121) being defined by at least one element including at least one of the SOC or a temperature of the secondary battery (41), the charge cycle degradation characteristic (122) defining a cycle degradation rate at a time of charging that is defined by at least one element including at least one of the SOC or a current rate of charging current of the secondary battery (41), finding a charging path that minimizes a total cost of paths between the nodes among charging paths from the present SOC at the charging start time to the target SOC at the charging end time via the nodes; and creating a charging plan based on the charging path found.
With this, it is possible to create a charging plan that minimizes the charging cost.
[Item 12] A computation system (1) includes: a path finder (113) which (i) sets a plurality of nodes in a state of charge (SOC) use range that is set when a secondary battery (41) provided in an electric moving body (3) is discharged, (i) sets a plurality of nodes in a dischargeable time period that is between a discharging start time and a discharging end time, and (iii) finds a discharging path from an upper limit SOC of the SOC use range at the discharging start time to a lower limit SOC of the SOC use range at the discharging end time via nodes among the plurality of nodes set in the SOC use range and the dischargeable time period; a discharging plan creator (1110) which creates a discharging plan based on the discharging path found; and a cost assigner (114) which refers to a storage degradation characteristic (121) and a discharge cycle degradation characteristic (123) to assign a degradation cost to each of paths between the plurality of nodes, the storage degradation characteristic (121) defined by at least one element including at least one of the SOC or a temperature of the secondary battery (41), the discharge cycle degradation characteristic (123) defining a cycle degradation rate at a time of discharging that is defined by at least one element including at least one of the SOC or a current rate of discharging current of the secondary battery (41). The path finder (113) finds a discharging path that minimizes a total degradation cost of the paths between the nodes.
With this, it is possible to create a discharging plan that minimizes the discharging cost.
[Item 13] A discharging plan creation program causing a computer to perform: setting a plurality of nodes in a state of charge (SOC) use range that is set when a secondary battery (41) provided in an electric moving body (3) is discharged, and setting a plurality of nodes in a dischargeable time period that is between a discharging start time and a discharging end time; referring to a storage degradation characteristic (121) and a discharge cycle degradation characteristic (123) to assign a degradation cost to each of paths between nodes among the plurality of nodes set in the SOC use range and the dischargeable time period, the storage degradation characteristic (121) being defined by at least one element including at least one of the SOC or a temperature of the secondary battery (41), the discharge cycle degradation characteristic defining a cycle degradation rate at a time of discharging that is defined by at least one element including at least one of the SOC or a current rate of discharging current of the secondary battery (41); finding a discharging path that minimizes a total degradation cost of paths between the nodes among discharging paths from an upper limit SOC of the SOC use range at the discharging start time to a lower limit SOC of the SOC use range at the discharging end time via the nodes; and creating a discharging plan based on the discharging path found.
With this, it is possible to create a discharging plan that minimizes the discharging cost.
Number | Date | Country | Kind |
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2020-179419 | Oct 2020 | JP | national |
Filing Document | Filing Date | Country | Kind |
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PCT/JP2021/038696 | 10/20/2021 | WO |