Patent Application
20250118982
Embodiments of this disclosure relate to energy storage systems, and more particular, to the use of second-life electric vehicle (EV) batteries in energy storage systems.
Electric vehicles (EVs) use batteries to store energy and provide power to an electric motor for propulsion. EV batteries typically have a defined lifespan during which the batteries can be safely used. After an EV battery has exceeded its lifespan, the battery is retired from use to ensure the safe operation of the EV. With the increasing penetration of EVs, the number of batteries retiring every year is expected to increase into the millions of battery packs.
The innovations described in the claims each have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of the claims, some prominent features of this disclosure will now be briefly described.
In a first aspect, a battery energy storage system is disclosed. The battery energy storage system may include, for example, a plurality of electric vehicle (EV) battery packs; a plurality of battery management system (BMS)-gateways each coupled to at least one of the EV battery packs, wherein each of the BMS-gateways is configured to communicate with the at least one EV battery pack via a communication protocol; and a modular energy management system (MEMS) configured to control the EV battery packs via the BMS-gateways.
In some embodiments, the EV battery packs are retired from use in electric vehicles. In some embodiments, the communication protocol is proprietary. In some embodiments, the each of the BMS-gateways is further configured to read one or more parameters from the at least one EV battery pack and provide the one or more parameters to the MEMS. In some embodiments, the each of the BMS-gateways is further configured to measure signals from the at least one EV battery pack. In some embodiments, the each of the BMS-gateways is further configured to provide the one or more parameters and the measured signals to the MEMS in real time. In some embodiments, the BMS-gateways are further configured to assign a unique identification to each of the EV battery packs. In some embodiments, the EV battery packs are installed into the battery energy storage system without being disassembled. In some embodiments, the EV battery packs are manufactured by a plurality of different original equipment manufacturers (OEMs) and the BMS-gateways are further configured to support the EV battery packs from the different OEMs. In some embodiments, the system further includes an inverter connecting the EV battery packs to an electrical grid. In some embodiments, the MEMS is configured to implement a model-based predict control (MPC) configured to collect one or more parameters relating to the EV battery packs from the BMS-gateways, and determine power flow of the system based on the collected parameters. In some embodiments, the MEMS is configured to execute pack-level control of the EV battery packs based on the determined power flow, and distribute power to each of the EV battery packs based on the collected parameters corresponding to each of the EV battery packs. In some embodiments, the MEMS is configured to detect an abnormal situation based on the collected parameters, and shut down the system in response to detecting the abnormal situation.
In a second aspect, a method of controlling a battery energy storage system is disclosed. The method may include, for example, communicating, using each of a plurality of battery management system (BMS)-gateways, with a corresponding one of a plurality of electric vehicle (EV) battery packs via a communication protocol; and controlling, using a modular energy management system (MEMS), the EV battery packs via the BMS-gateways.
In some embodiments, the method further includes installing the EV battery packs into the battery energy storage system after the EV battery packs are retired from use in electric vehicles. In some embodiments, the communication protocol is proprietary. In some embodiments, the method further includes reading, using each of the BMS-gateways, one or more parameters from the corresponding EV battery pack, and providing, using each of the BMS-gateways, the one or more parameters to the MEMS. In some embodiments, the method further includes measuring, using each of the BMS-gateways, signals from the corresponding EV battery pack. In some embodiments, the method further includes providing, using each of the BMS-gateways, the one or more parameters and the measured signals to the MEMS in real time. In some embodiments, the method further includes assigning, using each of the BMS-gateways, a unique identification to the corresponding EV battery pack.
With the increasing penetration of electric vehicles (EVs), millions of battery packs are expected to retire every year. After EV batteries are no longer suitable for vehicle use, EV batteries can still operate reliably in stationary energy storage applications and provide grid resiliency. Additionally, the availability of economically competitive and reliable energy storage is one of the largest barriers to expand the increasing use of renewables in the electrical grid. Thus, it is desirable to use retired EV batteries for “second-life” applications such as energy storage in the electrical grid, for example, within a battery energy storage system (BESS). Accordingly, the adoption of renewable energy can be increased by providing a cost-effective and reliable technique for incorporating second-life EV batteries into a BESS.
There are at least two approaches for reusing second-life EV battery packs in an energy storage system: using the original EV battery packs and disassembling the EV battery packs to obtain modules and/or cells.
However, it can be costly in terms of manpower, economics, and/or safety to disassemble and repack the EV batteries. These costs may be so high as to make the disassembly and repacking of the EV batteries infeasible. Compared to disassembling the battery packs to obtain modules and/or cells, using the original packs is more economically feasible because it saves the manpower and/or costs associated with the disassembly and regrouping of the batteries. Thus, it is desirable to provide systems and techniques which can reuse retired EV batteries for second-life applications without requiring disassembly and/or regrouping of EV batteries.
There may be certain challenges associated with reusing the whole EV battery pack as is. For example, when using the whole EV battery pack, battery cell information e.g., cell voltages, temperatures, current, etc. may not be accessible due to the original equipment manufacturer (OEM) including a proprietary battery management system (BMS) in the EV battery pack. That is, when the EV battery pack is not opened, the onboard battery management system (BMS) may be the only source that can provide battery cell information including the measure cell voltages and temperatures. However, the OEM does not typically provide access to the communication protocol(s) used to access the battery cell information from the onboard BMS. Therefore, it may not be possible to manage the EV battery packs using only the existing onboard BMS.
Another challenge is that the OEM communication protocol can be identical for each EV battery pack from the same OEM. Thus, when a plurality of EV battery packs from the same OEM are connected to the same main controller, the main controller may not be able to distinguish the information received from the onboard BMSs of the EV battery packs because the EV battery packs may share the same message ID.
Aspects of this disclosure relate to a BMS-Gateway and a modular energy management system (also referred to as an “energy management system”) that can address at least some of the above-described challenges.
As shown in
In certain embodiments, when constructing a BESS the retired EV battery packs 204 can be considered as a black box with no data and no control. For example, due to the use of proprietary BMSs, the retired EV battery packs 204 may not provide any data or be controllable without using the OEM's proprietary communication protocols. By using the BMS-gateway 202 as an intermediary to the EV battery packs 204, the modular energy management system 208 can interact with the BMS-gateway 202 in a manner similar to interacting with a fully functional battery pack with all the data, protection, and control needed for second-life use. In some implementations, the BMS-gateway 202 can appear the same as or similar to a repacked battery pack as shown in
Depending on the implementation, the BMS-gateway 202 can be configured communicate with the onboard BMS 206 of an EV battery pack 204 by cracking the communication protocol to achieve the battery cell voltages, temperatures, current, etc. The BMS-gateway 202 can also be configured to measure signals that the onboard BMS 206 does not or cannot provide, such as the DC-link voltage, current, and high voltage insulation, etc. In some embodiments, the BMS-gateway 202 further include built-in algorithm(s) configured to estimate battery state of charge (SOC), state of health (SOH), and/or to perform battery balance and protection. The BMS-gateway 202 can send of the collected and generated data to the energy management system 208 in real time to enable higher level management. The BMS-gateway 202 can also assign a unique ID for each EV battery pack 204 so that the energy management system 208 can monitor and control each EV battery pack 204 individually.
In some embodiments, there is at least one internal onboard manufacturer BMS inside of the EV battery pack 204 which gathers the cell-level data and sends them out using CANBUS messages with manufacturer-specific encoding. The BMS-gateway 202, after decoding (cracking) these messages, retrieves the data, reorganizes them, and sends them to the upper control using CANBUS messages with user-customized encoding. Therefore, for the cell-level data in this embodiment, the BMS-gateway 202 requires no extra hardware. Nonetheless, certain peripheral sensors can be added per user demand. These peripheral sensors would mainly gather pack-level lumped data such as total voltage and total current. The BMS-gateway 202 can also talk to these peripheral sensors using analog or digital I/O or ordinary communication protocols.
By using the BMS-gateway 202, the energy storage system 200 can directly use the EV battery pack 204 without needing to open and/or disassemble the EV battery pack 204. This can save time and costs, thereby making the reuse of EV battery packs 204 in energy storage systems 200 more economically feasible.
In certain embodiments, the BMS-gateway 202 can include hardware configured to support many different types of EV battery packs 204 (e.g., EV battery packs 204 from different OEMs). The BMS-gateway 202 can include built-in communication protocols to communicate to the onboard BMS 206 via a signal port on the onboard BMS 206.
In certain implementations, the MEMS 208 can be configured to implement an active and intelligent model-based predict control (MPC) in order to reduce utility bills. By executing the MPC, the MEMS 208 is configured to optimize or improve the utilization of the BESS. For example, the MEMS 208 can collect some or all of the information from the BMS-Gateway 202 and the existing system (including for example SOC, SOH, load power, and solar power) and determine the power flow of the BESS based on the collected information to maximize or improve the benefits of the system.
After the MPC has determined the power flow, the MEMS 208 can execute pack-level control and distribute power to each of the EV battery packs 204 in the BESS based on one or more of the corresponding parameters (e.g., SOC, SOH, maximum available power, etc.). By employing pack-level control, which allocates different power commands to each EV battery pack 204, the SOC of the EV battery packs 204 can be naturally balanced, while the lifespan of second-life EV batteries 204 can be extended at the same time. Moreover, the MEMS 208 can actively monitor the system status, including power level, voltage, current, temperature, and so on, to ensure a stable operation. Once an abnormal situation is detected, the MEMS 208 can shut down the BESS to protect the devices and prevent potential hazards. Finally, the MEMS 208 can further include a concise but informative user interface enabling users to monitor and, to some degree, control the system.
With reference to
The protection algorithm of the MEMS 208 may include different sub-algorithms, such as one or more of the following: battery protection, power devices protection, and system protection. The protection algorithms can be configured to protect the corresponding device(s) from one or more of the following conditions: over voltage, under voltage, over current, over power, over temperature, under temperature, device fault detection, and communication fault detection. The MEMS 208 may take different actions depending on the particular condition that the MEMS 208 determines a given device is at risk of experiencing or currently experiencing. The protection algorithm may provide information on the determined condition and corresponding device(s) to the control algorithm to address the condition.
The control algorithm of the MEMS 208 may include different sub-algorithms, such as one or more of the following: power/current limits, power flow control, energy distribution, and SOC balancing. The control sub-algorithms may be configured to control the EV battery packs 204 to meet the overall power and energy demands of the electrical grid 302 while also addressing any conditions identified by the protection algorithm.
The local analysis algorithm of the MEMS 208 may include different sub-algorithms, such as one or more of the following: SOC, SOH, available power capacity, available energy capacity, and proactive maintenance scheduling. In some embodiments, the control algorithm can be configured to use information generated by the local analysis algorithm to control the BESS. The MEMS 208 can also be configured to display at least some of the information determined by the local analysis algorithm to a user.
The system monitoring algorithm of the MEMS 208 may include different sub-algorithms, such as one or more of the following: system parameter displaying, data logging, emergency stop, and external control. The MEMS 208 can also be configured to display at least some of the logged information by the system monitoring algorithm to a user. The system monitoring algorithm may also be configured to receive input from the user, including whether to perform an emergency stop or other external controls for controlling the BESS.
One of the CAN channels can be used to communicate with the MEMS 208. The other CAN and LIN channels can be configured to communicate with the onboard BMS 206 or vehicle control unit (VCU) of the corresponding EV battery pack 204 to get the battery cell voltages and temperatures. The BMS-gateway 202 can also be configured to provide general control and measurement functions. For example, the 8 channels HSD and LSD can be configured to control the relays, DC contactors, fans, pumps, cooling, and/or heating systems, etc. of the corresponding EV battery pack 204. The BMS-gateway 202 can also be configured to provide general measurement functions via the 9 IO/PWM, 6 ADC, and 4 NTC temperature measurement channels. The BMS-Gateway 202 can further be configured to measure the DC voltage and current of the corresponding EV battery pack 204 as well as detect the high voltage isolation to the EV battery pack 204 shell.
The BMS-gateway's 202 hardware is versatile and is configured to be adapted to many different commercial EV battery packs 204. However, different EV battery packs 204 may have different communication protocols. For example, an EV battery pack 204 may use proprietary communication protocol which can be either provided by the OEM or cracked by studying the communication process. Many BMS communication protocols are not encrypted, and therefore can be cracked.
The BMS-gateway 202 is configured to continuously communicate with the onboard BMS 206 of the corresponding EV battery pack 204 and measure the signals described above. Thus, all or substantially all of the EV battery pack's 204 data can be sent to the MEMS 208 periodically, e.g., once a second by the BMS-gateway 202, or at other frequencies and/or at irregular intervals.
There are multiple possible embodiments for the MEMS 208 hardware. One example embodiment is a desktop/laptop with basic I/O peripherals such as screen and keyboard/mouse. Another example embodiment is a microprocessor-based embedded controller with graphic interface, such that the user can interact with the system.
The MEMS 208 hardware includes a plurality of communication interfaces configured to communicate with the BMS-gateway 202 and components of the power control system (PCS). In certain embodiments, the MEMS 208 hardware is configured to be connected to the BMS-gateway 202 through a CAN bus and to the components in the PCS through a router and Ethernet cables.
The MEMS 208 software running on the MEMS 208 hardware can be configured to implement a comprehensive BESS management software. The MEMS 208 software can be developed to be run on the MEMS 208 hardware and can be configured to cause the MEMS 208 hardware to interact with each of the BMS-gateway 202/EV battery pack 204 combinations and with each component of the PCS using the corresponding communication protocols. In the embodiment shown in
Methods described herein may be implemented as software and executed by a general purpose computer. For example, such a general purpose computer may include a control unit/controller or central processing unit (“CPU”), coupled with memory, EPROM, and control hardware. The CPU may be a programmable processor configured to control the operation of the computer and its components. For example, CPU may be a microcontroller (“MCU”), a general purpose hardware processor, a digital signal processor (“DSP”), an application specific integrated circuit (“ASIC”), field programmable gate array (“FPGA”) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor can be a microprocessor, but in the alternative, the processor can be any processor, controller, or microcontroller. A processor can also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Such operations, for example, may be stored and/or executed by an onsite or remote memory.
While not specifically shown, the general computer may include additional hardware and software typical of computer systems (e.g., power, cooling, operating system) is desired. In other implementations, different configurations of a computer can be used (e.g., different bus or storage configurations or a multi-processor configuration). Some implementations include one or more computer programs executed by a programmable processor or computer. In general, each computer may include one or more processors, one or more data-storage components (e.g., volatile or non-volatile memory modules and persistent optical and magnetic storage devices, such as hard and floppy disk drives, CDROM drives, and magnetic tape drives), one or more input devices (e.g., mice and keyboards), and one or more output devices (e.g., display consoles and printers).
While the invention has been described in terms of several embodiments, those skilled in the art will recognize that the invention is not limited to the embodiments described, can be practiced with modification and alteration within the spirit and scope of the appended claims. In particular, the disclosure can be modified in terms of hardware and materials used to form the apparatus described herein. Any conventional or otherwise known materials could be implemented with the scope of the present disclosure. The description is thus to be regarded as illustrative instead of limiting.
This application is a continuation of International Application No. PCT/US2023/026755, filed Jun. 30, 2023, which is based upon and claims the benefit of U.S. Provisional Application No. 63/358,759, filed Jul. 6, 2022 and U.S. Provisional Application No. 63/376,027, filed Sep. 16, 2022. The foregoing applications are hereby incorporated by reference in their entireties.
This invention was made with State of California support under California Energy Commission grant number EPC 19-053. The Energy Commission has certain rights to this invention.
| Number | Date | Country | |
|---|---|---|---|
| 63358759 | Jul 2022 | US | |
| 63376027 | Sep 2022 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/US2023/026755 | Jun 2023 | WO |
| Child | 18987671 | US |
