The present invention relates to monitoring battery state of charge, and more specifically to systems and methods for real-time monitoring of battery state of charge.
The accurate monitoring of a battery system state of charge (SOC) is a common issue in battery applications. There are four main methods for monitoring SOC. One method is to determine SOC by dividing the charge left in battery system divided by the full charge capacity of the battery system. However, it is generally non-trivial to measure the charge left in the battery system directly, especially in a dynamic environment. An alternate form of this first method is to calculate the integral of current over time as the charge in the battery system changes. However, in such a method, the current sensor tolerance is generally limited and errors will typically accumulate. Further, the initial SOC, full charge capacity, and the battery efficiencies during charge and discharge cycles are difficult to obtain. Additionally, using such a method becomes extremely difficult in circumstances where charging and discharging occur randomly, as in hybrid electric vehicles, or where there are no clear charge/discharge cycles.
A second method is to use the relation of electric motive force (EMF) and SOC of a battery system. That is, using EMF to decide SOC, since EMF and SOC have a monotonic relationship in many types of battery systems. In particular, this method relies on using the open circuit voltage (OCV) as the EMF. However, due to the capacitance in a battery, it can take several hours of relaxing (i.e., zero current draw) to let OCV approach EMF, rendering such a method unsuitable for real-time monitoring.
A third method is to use the first method to estimate SOC and use the second method to adjust the estimate of SOC. However, since such a method still relies on OCV, it is generally difficult to provide a period of operational time with zero current to provide an accurate measure of EMF, resulting in inaccurate measurement of SOC.
The fourth method is Extended Kalman Filter Method. This method requires an extensive calculation on micro controller, which is a bottle neck for small micro controller chips.
In an exemplary embodiment of the present disclosure, systems and methods for monitoring a state of charge of a battery are disclosed.
In another exemplary embodiment of the present disclosure, a method for monitoring a state-of-charge (SOC) for a battery connected to a load is provided. The method comprising determining with an electronic controller an estimation of the SOC of the battery; measuring a terminal voltage of the battery; measuring a current of the battery; and determining with an electronic controller a first value of at least one battery parameter from a database including a plurality of values of the at least one battery parameter. The first value of the at least one battery parameter being based on the estimation of the SOC of the battery. The method further comprising determining with the electronic controller a calculated terminal voltage of the battery; and determining with the electronic controller an updated estimation of the SOC of the battery based at least on the first value of the at least one battery parameter, the measured terminal voltage, and the calculated terminal voltage.
In a further exemplary embodiment of the present disclosure, a system for monitoring a state-of-charge (SOC) of a battery system connected to a load is provided. The system comprising at least one measurement element configured for measuring a terminal voltage and a current of said battery system during a sample time and a storage element configured for storing at least an estimation of the SOC of the battery, the measured terminal voltage of the battery, the measured current of the battery, and a plurality of values of at least one battery parameter. The plurality of values of the at least one battery parameter being based related to a plurality of values of the SOC of the battery. The system further comprising a processing element operatively coupled to said measurement element and said storage element. The processing element configured to determine a calculated terminal voltage of the battery; and determine an updated estimation of the SOC of the battery based at least on a first value of the plurality of values of the at least one battery parameter, the measured terminal voltage, and the calculated terminal voltage. The first value corresponding to the estimation of the SOC of the battery.
In yet another exemplary embodiment of the present disclosure, a computer readable medium including a plurality of instructions related to monitoring a state-of-charge (SOC) for a battery connected to a load is provided. The plurality of instructions being executable by an electronic controller to perform the steps of determining an estimation of the SOC of the battery; determining a first value of at least one battery parameter from a database including a plurality of values of the at least one battery parameter, the first value of the at least one battery parameter being based on the estimation of the SOC of the battery; determining a calculated terminal voltage of the battery; and determining an updated estimation of the SOC of the battery based at least on the first value of the at least one battery parameter, a measured terminal voltage, and the calculated terminal voltage.
In still another exemplary embodiment of the present disclosure, a method for monitoring a state-of-charge (SOC) for a battery connected to a load is provided. The method comprising: measuring a terminal voltage and a charge/discharge (CD) current of said battery; providing a plurality of pre-defined battery parameters associated with a plurality of SOC values; computing a calculated terminal voltage based on a stored polarization value, a stored hysteresis value, and said plurality of pre-defined parameters associated with a stored SOC value; and calculating a updated SOC value based on said measured terminal voltage, said calculated terminal voltage value, said CD current, and a predefined gain value associated with said stored SOC value.
In still a further exemplary embodiment of the present disclosure, a system for monitoring a state-of-charge (SOC) of a battery system connected to a load is provided. The system comprising at least one measurement element configured for measuring a terminal voltage and a charge/discharge (CD) current of said battery system during a sample time; a storage element configured for storing at least a previous SOC value, a plurality of pre-defined battery parameters associated with a plurality of SOC values, and a plurality of pre-defined gain values associated with said plurality of SOC values; a processing element communicatively coupled to said measurement element and said storage element. The processing element configured for computing a calculated terminal voltage based on a stored polarization value, a stored hysteresis value, and said plurality of pre-defined parameters associated with a stored SOC value, and calculating a updated SOC value based on said measured terminal voltage, said calculated terminal voltage value, said CD current, and a one of said plurality of pre-defined gain values associated with said stored SOC value.
In yet a further exemplary embodiment of the present disclosure, a computer-readable storage medium, having stored thereon a computer program for monitoring a state-of-charge (SOC) of a battery connected to a load, is provided. The computer program comprising a plurality of instructions executable by a computer. The plurality of instructions comprising code sections for performing the steps of accessing a plurality of pre-defined battery parameters and a plurality of pre-defined gain values for a plurality of SOC values; measuring a terminal voltage and a charge/discharge (CD) current of said battery; calculating updated terminal voltage, polarization, and hysteresis values for said battery based on said discharge current, a stored polarization value, a stored hysteresis value, and a portion of said plurality of parameters associated with a stored SOC value; generating an adjusted SOC value based on said obtained terminal voltage, said updated terminal voltage value, and one of said plurality of gain values associated with said stored SOC value; and computing an updated SOC value based on said adjusted SOC value.
In still a further exemplary embodiment of the present disclosure, a battery assembly is provided. The battery system comprising a battery system comprising at least one battery cell; and a monitoring system for monitoring a state of charge (SOC) of the battery system. The monitoring system comprises at least one measurement element configured for measuring a terminal voltage and a charge/discharge (CD) current of said battery system during a sample time; a storage element configured for storing at least a previous SOC value, a plurality of pre-defined battery parameters associated with a plurality of SOC values, and a plurality of pre-defined gain values associated with said plurality of SOC values; and a processing element configured for computing a calculated terminal voltage based on a stored polarization value, a stored hysteresis value, and said plurality of pre-defined parameters associated with a stored SOC value, and calculating a updated SOC value based on said measured terminal voltage, said calculated terminal voltage value, said CD current, and a one of said plurality of pre-defined gain values associated with said stored SOC value.
In still yet a further exemplary embodiment of the present disclosure, a system is provided. The system comprising a battery system comprising at least one battery cell; a load electrically coupled to said battery system; and a monitoring system for monitoring a state of charge (SOC) of the battery system. The monitoring system comprises at least one measurement element configured for measuring a terminal voltage and a charge/discharge (CD) current of said battery system during a sample time; a storage element configured for storing at least a previous SOC value, a plurality of pre-defined battery parameters associated with a plurality of SOC values, and a plurality of pre-defined gain values associated with said plurality of SOC values; and a processing element configured for computing a calculated terminal voltage based on a stored polarization value, a stored hysteresis value, and said plurality of pre-defined parameters associated with a stored SOC value, and calculating a updated SOC value based on said measured terminal voltage, said calculated terminal voltage value, said CD current, and a one of said plurality of pre-defined gain values associated with said stored SOC value.
The above-mentioned and other features and advantages of this disclosure, and the manner of attaining them, will become more apparent and the invention itself will be better understood by reference to the following description of embodiments of the invention taken in conjunction with the accompanying drawings, wherein:
Corresponding reference characters indicate corresponding parts throughout the several views. The exemplifications set out herein illustrate exemplary embodiments of the invention and such exemplifications are not to be construed as limiting the scope of the invention in any manner.
The embodiments disclosed herein are not intended to be exhaustive or to limit the invention to the precise forms disclosed in the following detailed description. Rather, the embodiments are chosen and described so that others skilled in the art may utilize their teachings. While the present invention primarily involves the monitoring of the state of charge of batteries for a vehicle or energy grid storage system, it should be understood, that the invention may have application for batteries which provide power to other devices.
The present invention is not limited by the illustrated ordering of acts or events, as some acts may occur in different orders and/or concurrently with other acts or events. Furthermore, not all illustrated acts or events are required to implement a methodology in accordance with the present invention.
Kalman filter-based methods for control and monitoring of systems are based on a form of feedback control. First, the filter estimates the state of the system at a first time and then obtains feedback in the form of some type of measurements. Thus, Kalman filter methods rely on projecting a current state estimate ahead in time and adjusting the projected estimate using actual measurements at that time. In order to provide adjustments for the projected estimate, Kalman filter methods require several matrix calculations (operations) including predict a state (vector), predict estimate covariance(matrix), update measurement residual(matrix), update covariance(matrix), calculate gain matrix, update state estimate(vector), update estimate covariance(matrix), calculation in iteration. In general, these computations include the determination of inverse matrix. As a result, a conventional Kalman filter method is commonly computationally intensive and prone to failure due to ill conditions in the matrices and/or divergence during the various iterations.
As described herein, one or more reference tables, see databases 140-148 in
As shown in
System 100 further includes a SOC monitor 106 for monitoring the SOC of battery 102. As shown in
As described above, memory 114 is configured to store various values. Referring to
In addition, memory 114 stores various measured values 132. Exemplary measured values include a charge or discharge current (I) of the battery, a terminal voltage (Vt) of the battery, and a temperature (T) associated with the battery. Memory 114 further includes one or more databases which provide additional battery parameters based on the current SOC (Sk) value associated with the battery or based on the current SOC (Sk) value associated with the battery and the temperature (T) associated with the battery. Exemplary database arrangements include an array of values, a look-up table, and other suitable arrangements for organizing data.
In an exemplary embodiment, memory 114 includes a SOC_T_EMF database 140, a SOC_T_POLARIZATION database 142, a SOC_T_HYSTERESIS database 144, a SOC_T_RESISTANCE database 146, and a SOC_T_GAIN database 148. Databases 140-148 are queried or otherwise accessed by SOC software 136 of the SOC monitor 106 as described herein in relation to the processing sequences of
Referring to
In one embodiment, the vehicle propulsion system 160 includes an electric motor which receives electrical energy from a battery system 164 over a vehicle propulsion bus. The electric motor is operatively coupled to one or more ground engaging members 152 through a power transfer system. Exemplary power transfer systems include transmissions and drive shafts. Battery system 164 includes a plurality of batteries, such as represented by battery 102 in
In the illustrated embodiment, battery system 164 provides at least a portion of the motive power for vehicle 150. In one embodiment, vehicle propulsion system 160 converts the power provided by batteries 102 to AC to drive an AC electric motor. In one example, battery system 164 provides at least about 200 V to vehicle propulsion system 160. In one example, battery system 164 provides up to about 400 V to vehicle propulsion system 160. In one example, battery system 164 provides in the range of about 240 V to about 400 V to vehicle propulsion system 160.
Vehicle 150 further includes a battery management system 168 which monitors the battery system 164 and controls the operation of the battery system 164. In one embodiment, the SOC monitor 106 is a part of the battery management system 168. In one embodiment, the SOC monitor 106 is separate from and communicates with the battery management system 168.
Vehicle 150 further includes a charging system 180 which provides a charge current to battery system 164. Exemplary charging systems include a generator, a plug-in connection, and other suitable devices for charging battery system 164.
As mentioned in connection with
Referring to
The terminal voltage (Vt) and the discharge current (I) for the battery 102 are measured, as represented by block 206. In the illustrated embodiment of
After the initial values of (Sk, pk, and hk) and values for Vt and I are determined, additional parameters may be determined, as represented by block 208. In one embodiment, a calculated terminal voltage (Vtc) is determined. The difference in the calculated terminal voltage (Vtc) and the measured terminal voltage (Vt) may then be used to adjust the value of the SOC as discussed herein. An exemplary processing sequence for determining a calculated terminal voltage (Vtc) is illustrated in
Referring to
The polarization coefficient value (ep) for the stored SOC (Sk) is retrieved by controller 108, as represented by block 306 and as illustrated in
The hysteresis coefficient value (eh) for the stored SOC (Sk)) is retrieved by controller 108, as represented by block 308 and as illustrated in
The internal resistance value (R) for the stored SOC (Sk)) is retrieved by controller 108, as represented by block 310 and as illustrated in
The values for the databases accessed by controller 108, as represented by blocks 304-310, may be generated analytically or experimentally. Further, the databases may be stored locally with controller 108 or remotely and accessible by controller 108 over a network.
In some instances the SOC value of Sk may not correspond to an SOC value in one or more of databases 140-148. In this case, in one embodiment, controller 108 selects a value for the parameter to be returned based on one or more values of SOC provided in the respective database. For example, a value may be selected by interpolation, based on Sk and the SOC values in the table and their corresponding values for the parameter to be returned. Alternatively, a value may be selected by rounding Sk to a next tabulated value and retrieving the corresponding value. In yet another method, a proximity method can be used. That is, a value associated with an SOC value closest to Sk may be used. Other exemplary methods may be used to determine values based on the value of Sk. The same interpolation and other exemplary methods apply to the stored temperature values as well.
As represented by block 312, an updated hysteresis value (hk+1) is determined by controller 108. In one embodiment, an updated hysteresis value (hk+1) is determined in accordance with equation 1:
hk+1=ehsign(I)(1−e−|μIδt|)+hke−|μIδt| (1)
wherein hk+1 is the hysteresis value at (k+1)th iteration, eh is the hysteresis coefficient, I is the current (positive when charge, negative when discharge), μ is the hysteresis decay constant, δt is the sampling time, hk is the hysteresis value at kth iteration, and sign( ) is the sign function which is 1 when the value of I is greater than zero, −1 when the value of I is less than zero, 0 when I is zero.
As represented by block 314, an updated polarization value (pk+1) is determined by controller 108. In one embodiment, an updated polarization value (pk−1) is determined in accordance with either equation 2 or equation 3 depending on a value of the measured current (I).
pk+1=epsign(I)(1−e−Kδt)+pke−Kδt for I>currentlimit1 (2)
pk+1pke−Kδt for |I|≤current limit 1 (3)
wherein pk+1 is the polarization value at (k+1)th iteration, ep is the polarization coefficient, I is the current (positive when charge, negative when discharge), K is the polarization decay constant, δt is the sampling time, pk is the polarization value at kth iteration, and sign( ) is the sign function which is 1 when the value of I is greater than zero and −1 when the value of I is less than zero, 0 when I is zero. The current limit 1 is a fraction of the C-rate current of the battery. In one example the value of current limit 1 is about 2 percent of 1 C to about 3 percent of 1 C. For example, 1 C is 15 A for some batteries and the current limit 1 may be selected as 0.4 A. Under such current limit, the charge/discharge is very small and may be neglected.
As represented by block 314, a calculated terminal voltage (Vtc) is determined by controller 108. In one embodiment, a calculated terminal voltage (Vtc) is determined in accordance with equation 4:
Vtc=Ef+RI+hk+pk (4)
wherein Vtc is the calculated terminal voltage, Ef is the electric motive force value, R is the internal resistance value, I is the current (positive when charge, negative when discharge), hk is the hysteresis value at kth iteration, and pk is the polarization value at kth iteration.
Returning to
Ska=Sk+g(Vt−Vtc) (5)
wherein Sk+1 is the adjusted SOC value at kth iteration, Sk is the SOC value at kth iteration, g is the SOC gain coefficient value, Vt is the measured terminal voltage value, and Vtc is the calculated terminal voltage value.
An updated SOC value (Sk+1) may be determined, as represented by block 214. In one embodiment, an updated SOC value (Sk+1) is determined in accordance with equation 6:
wherein Sk+1 is the updated SOC value corresponding to the (k+1)th iteration, Ska is the adjusted SOC value at kth iteration, γ is the efficiency value of charge and discharge (may be different during charge and discharge), I is the current value (positive when charge, negative when discharge), Q is the full charge capacity value of the battery system, and δt is the sampling time interval.
Either Sk+1 or Ska may be reported by controller 108 as the SOC value. Controller 108 then stores the values for the k+1 iteration as the new k iteration values and determines the next values for the k+1 iteration.
The machine may comprise various types of computing systems and devices, including a server computer, a client user computer, a personal computer (PC), a tablet PC, a laptop computer, a desktop computer, a control system, a network router, switch or bridge, or any other device capable of executing a set of instructions (sequential or otherwise) that specifies actions to be taken by that device. It is to be understood that a device of the present disclosure also includes any electronic device that provides voice, video or data communication. Further, while a single computer is illustrated, the phrase “computer system” shall be understood to include any collection of computing devices that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.
The computer system 400 may include a processor 402 (such as a central processing unit (CPU), a graphics processing unit (GPU, or both), a main memory 404 and a static memory 406, which communicate with each other via a bus 408. The computer system 400 may further include a display unit 410, such as a video display (e.g., a liquid crystal display or LCD), a flat panel, a solid state display, or a cathode ray tube (CRT)). The computer system 400 may include an alphanumeric input device 412 (e.g., a keyboard), a cursor control device 414 (e.g., a mouse), a disk drive unit 416, a signal generation device 418 (e.g., a speaker or remote control) and a network interface device 420.
The disk drive unit 416 may include a computer-readable medium 422 on which is stored one or more sets of instructions 424 (e.g., software code) configured to implement one or more of the methodologies, procedures, or functions described herein. The instructions 424 may also reside, completely or at least partially, within the main memory 404, the static memory 406, and/or within the processor 402 during execution thereof by the computer system 400. The main memory 404 and the processor 402 also may constitute machine-readable media.
Dedicated hardware implementations including, but not limited to, application-specific integrated circuits, programmable logic arrays, and other hardware devices may likewise be constructed to implement the methods or processing sequences described herein. Applications that can include the apparatus and systems of the various embodiments disclosed herein broadly include a variety of electronic and computer systems. Some embodiments implement functions in two or more specific interconnected hardware modules or devices with related control and data signals communicated between and through the modules, or as portions of an application-specific integrated circuit. Thus, the exemplary system is applicable to software, firmware, and hardware implementations.
In accordance with various embodiments of the present disclosure, the methods described herein may be stored as software programs in a computer-readable medium and may be configured for running on a computer processor. Furthermore, software implementations may include, but are not limited to, distributed processing, component/object distributed processing, parallel processing, virtual machine processing, which may also be constructed to implement the methods described herein.
The present disclosure contemplates a computer-readable medium containing instructions 424 or that receives and executes instructions 424 from a propagated signal so that a device connected to a network environment 426 may send or receive data and that may communicate over the network 426 using the instructions 424. The instructions 424 may further be transmitted or received over a network 426 via the network interface device 420.
While the computer-readable medium 422 is shown in an exemplary embodiment to be a single storage medium, the term “computer-readable medium” should generally be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present disclosure.
The term “computer-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories such as a memory card or other package that houses one or more read-only (non-volatile) memories, random access memories, or other re-writable (volatile) memories; magneto-optical or optical medium such as a disk or tape; as well as devices including a tangible transmission medium for carrying carrier wave signals such as a signal embodying computer instructions; and/or a digital file attachment to e-mail or other self-contained information archive or set of archives considered to be a distribution medium equivalent to a tangible storage medium. Accordingly, the disclosure is considered to include any one or more of a computer-readable medium or a distribution medium, as listed herein and to include recognized equivalents and successor media, in which the software implementations herein are stored.
The disclosed processing sequences were compared to observed SOC values for a battery system. An A306 battery cell available from EnerDel located in Indianapolis, Ind. was tested with the Hybrid Pulse Power Characterization Test (“HPPC”) procedure and other test cycles.
The HPPC test consists of a series of discharge and regen pulses performed at every 10% depth of discharge (DOD) increment, with an hour rest at open circuit at each increment to ensure that the battery has electrochemically equilibrated. The open circuit voltage is determined after the hour rest. In addition, the battery current (I) and the terminal voltage (Vt) are monitored throughout the testing to provide input to the disclosed processing sequences.
Referring to Tables I-III, the disclosed processing sequences are compared to observed SOC values. In column (A) of each of Tables I-III, an observed SOC for the A306 battery cell is provided. The observed SOC is determined based on the measured open circuit voltage (OCV) of the A306 cell. In columns (B)-(D), SOC values determined by the disclosed processing sequences are provided. Column (B) provides the maximum SOC value determined during the one hour after respective discharge interval. Column (C) provides the minimum SOC value determined during the one hour after the respective discharge interval. Column (D) provides the determined SOC value at one hour after the discharge interval.
In one embodiment, the disclosed processing sequences have an absolute error of about 3 percent of the observed data. In one embodiment, the disclosed processing sequences have an absolute error of up to about 3 percent of the observed data.
While this invention has been described as having exemplary designs, the present invention can be further modified within the spirit and scope of this disclosure. This application is therefore intended to cover any variations, uses, or adaptations of the invention using its general principles. Further, this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this invention pertains and which fall within the limits of the appended claims.
This application is a national stage of PCT Patent Application Serial No. PCT/US2011/033582, filed on Apr. 22, 2011, which claims the benefit of U.S. Application No. 61/326,881 filed on Apr. 22, 2010, the disclosures of which are expressly incorporated herein by reference.
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