Fast charging control based on modified equivalent circuit model

Abstract

The present disclosure relates to fast charging control based on modified equivalent circuit model. The method includes receiving a cathode voltage response predicted by a cathode equivalent circuit model (ECM) of a battery cell, and an anode voltage response predicted by an anode ECM of the battery cell. The method also includes determining a cathode resistance voltage drop across a cathode ohmic resistor, an anode resistance voltage drop across an anode ohmic resistor, a cathode electrode voltage drop across a cathode resistor-capacitor, and an anode electrode voltage drop across an anode resistor-capacitor. The method also includes determining whether the cathode potential exceeds a cathode potential threshold, and whether the anode potential falls below an anode potential threshold. When the cathode potential exceeds the cathode threshold potential, or the anode potential falls below the anode potential threshold, the method includes modifying a charging current supplied to the battery cell.

Description

[0001] introduce

[0002] The information provided in this section is for the purpose of presenting the overall context of this disclosure. The work of the inventors currently named is neither expressly nor implicitly acknowledged as prior art to this disclosure, to the extent described in this section and in any other way that may not conform to the description of the prior art at the time of filing.

[0003] This disclosure generally relates to fast charging control utilizing a modified equivalent circuit model. Specifically, fast charging for electric vehicles (EVs) is a process that allows EV batteries to be charged at a significantly higher rate compared to standard charging methods. This is typically achieved using a direct current (DC) fast charger that can deliver power levels ranging from 50 kW to over 350 kW. The fast charging process involves complex power electronics and communication protocols between the charging station and the vehicle's systems, which manage charging parameters such as voltage, current, and temperature. Fast charging is particularly beneficial for reducing charging-related downtime, making EVs more convenient for long-distance travel and daily use.

[0004] However, accurate monitoring and control of fast-charging parameters are essential to limiting the risks associated with this process. For example, there is a potential for EV batteries to overheat, which can affect battery performance and contribute to battery degradation. Additionally, improper management of charging parameters can lead to lithium plating, a phenomenon where lithium ions deposit on the anode surface instead of embedding within the anode material. This can reduce battery capacity, increase internal resistance, and ultimately shorten battery life. Therefore, precise monitoring and adjustment of fast-charging parameters are crucial for mitigating these risks and ensuring optimal performance and durability of EV batteries. Summary of the Invention

[0005] One aspect of this disclosure provides a computer-implemented method for fast charging control with a modified equivalent circuit model, which, when executed on data processing hardware, causes the data processing hardware to perform operations including: receiving a cathode voltage response predicted by a cathode equivalent circuit model (ECM) of a battery cell, the cathode ECM including a cathode open-circuit voltage (OCV), a cathode ohmic resistor, and at least one cathode resistor-capacitor pair; and receiving an anode voltage response predicted by an anode ECM of the battery cell, the anode ECM including an anode OCV, an anode ohmic resistor, and at least one anode resistor-capacitor pair. The operations also include determining a cathode resistance voltage drop across the cathode ohmic resistor, determining an anode resistance voltage drop across the anode ohmic resistor, determining a cathode electrode voltage drop across at least one cathode resistor-capacitor pair, and determining an anode electrode voltage drop across at least one anode resistor-capacitor pair. The operation further includes determining whether the cathode potential of the battery cell exceeds a cathode potential threshold based on the cathode resistance voltage drop and the cathode electrode voltage drop, and determining whether the anode potential of the battery cell drops below the anode potential threshold based on the anode resistance voltage drop and the anode electrode voltage drop. When one or more cathode potentials of the battery cell exceed the cathode threshold potential, or when the anode potential of the battery cell drops below the anode potential threshold, the operation also includes modifying the charging current supplied to the battery cell.

[0006] Implementations of this disclosure may include one or more of the following optional features. In some implementations, the operation further includes determining a lithiated cathode state and a lithiated anode state, generating a modified lithiated anode state based on the equilibrium potential of the battery cell, and generating a modified lithiated cathode state based on the equilibrium potential of the battery cell. In these implementations, determining whether the cathode potential of the battery cell exceeds a cathode potential threshold is further based on the modified lithiated cathode state. Additionally or alternatively, determining whether the anode potential of the battery cell drops below an anode potential threshold is further based on the modified lithiated anode state.

[0007] In some examples, the resistance measured by the cathode ohm resistor is modified by Butler-Volmer simulation. In some implementations, the resistance measured by the anode ohm resistor is modified by Butler-Volmer simulation. In some examples, the operation further includes measuring the resistance of at least one cathode resistor-capacitor pair, and dynamically updating the capacitor of at least one cathode resistor-capacitor pair based on the measured resistance and time constant.

[0008] In some implementations, the operation further includes measuring the resistance of at least one anode resistor-capacitor pair and dynamically updating the capacitor of at least one anode resistor-capacitor pair based on the measured resistance and a time constant. In some examples, the operation further includes receiving the separator overpotential measured by the separator ECM of the battery cell and generating a virtual reference electrode of the battery cell based on the separator overpotential and the anode potential. In some implementations, the battery cell supplies power to the vehicle.

[0009] Another aspect of this disclosure provides a system including data processing hardware and memory hardware in communication with the data processing hardware. The memory hardware stores instructions that, when executed by the data processing hardware, cause the data processing hardware to perform operations including receiving a cathode voltage response predicted by a cathode equivalent circuit model (ECM) of a battery cell, the cathode ECM including a cathode open-circuit voltage (OCV), a cathode ohmic resistor, and at least one cathode resistor-capacitor pair; and receiving an anode voltage response predicted by an anode ECM of the battery cell, the anode ECM including an anode OCV, an anode ohmic resistor, and at least one anode resistor-capacitor pair. The operations also include determining a cathode resistance voltage drop across the cathode ohmic resistor, determining an anode resistance voltage drop across the anode ohmic resistor, determining a cathode electrode voltage drop across at least one cathode resistor-capacitor pair, and determining an anode electrode voltage drop across at least one anode resistor-capacitor pair. The operation further includes determining whether the cathode potential of the battery cell exceeds a cathode potential threshold based on the cathode resistance voltage drop and the cathode electrode voltage drop, and determining whether the anode potential of the battery cell drops below the anode potential threshold based on the anode resistance voltage drop and the anode electrode voltage drop. When one or more cathode potentials of the battery cell exceed the cathode threshold potential, or when the anode potential of the battery cell drops below the anode potential threshold, the operation also includes modifying the charging current supplied to the battery cell.

[0010] This aspect may include one or more of the following optional features. In some implementations, the operation further includes determining the lithiation of the cathode state and the lithiation of the anode state, generating a modified lithiation of the anode state based on the equilibrium potential of the cell, and generating a modified lithiation of the cathode state based on the equilibrium potential of the cell. In these implementations, determining whether the cathode potential of the cell exceeds a cathode potential threshold is further based on the modified lithiation of the cathode state. Additionally or alternatively, determining whether the anode potential of the cell drops below an anode potential threshold is further based on the modified lithiation of the anode state.

[0011] In some examples, the resistance measured by the cathode ohm resistor is modified by Butler-Volmer simulation. In some implementations, the resistance measured by the anode ohm resistor is modified by Butler-Volmer simulation. In some examples, the operation further includes measuring the resistance of at least one cathode resistor-capacitor pair, and dynamically updating the capacitor of at least one cathode resistor-capacitor pair based on the measured resistance and time constant.

[0012] In some implementations, the operation further includes measuring the resistance of at least one anode resistor-capacitor pair, and dynamically updating the capacitor of at least one anode resistor-capacitor pair based on the measured resistance and a time constant. In some examples, the operation further includes receiving the separator overpotential measured by the separator ECM of the battery cell, and generating a virtual reference electrode of the battery cell based on the separator overpotential and the anode potential. In some implementations, the battery cell supplies power to the vehicle.

[0013] This disclosure also relates to the following technical solutions.

[0014] Option 1. A computer-implemented method executed on data processing hardware, the method causing the data processing hardware to perform operations including:

[0015] Receive the cathode voltage response predicted by the cathode equivalent circuit model (ECM) of the battery cell, which includes the cathode open-circuit voltage (OCV), a cathode ohmic resistor and at least one cathode resistor-capacitor pair;

[0016] Receive the anode voltage response predicted by the anode ECM of the battery cell, the anode ECM including an anode OCV, an anode ohmic resistor and at least one anode resistor-capacitor pair;

[0017] Determine the cathode resistance voltage drop across the cathode ohmic resistor;

[0018] Determine the voltage drop across the anode resistor of the anode ohmic resistor;

[0019] Determine the cathode electrode voltage drop across at least one cathode resistor-capacitor pair;

[0020] Determine the anode voltage drop across at least one anode resistor-capacitor pair;

[0021] Determine whether the cathode potential of the battery cell exceeds the cathode potential threshold based on the cathode resistance voltage drop and the cathode electrode voltage drop;

[0022] Determining whether the anode potential of the battery cell has dropped below the anode potential threshold based on the anode resistance voltage drop and the anode electrode voltage drop; and

[0023] When one or more cathode potentials of the battery cell exceed the cathode threshold potential, or when the anode potential of the battery cell drops below the anode potential threshold, the charging current supplied to the battery cell is modified.

[0024] Option 2. The method according to Option 1, wherein the operation further includes:

[0025] Determine the cathode state and the anode state of lithiation;

[0026] Modified lithiation anode state is generated based on the equilibrium potential of the battery cell; and

[0027] The cathode state of lithiation is modified based on the equilibrium potential of the battery cell.

[0028] Option 3. According to the method of Option 2, wherein determining whether the cathode potential of the battery cell exceeds the cathode potential threshold is further based on the modified cathode state of lithiation.

[0029] Option 4. According to the method of Option 2, wherein determining whether the anode potential of the battery cell has dropped below the anode potential threshold is further based on the modified lithiation anode state.

[0030] Option 5. The method described in Option 1, wherein the resistance measured by the cathode ohm resistor is modified by Butler-Volmer simulation.

[0031] Option 6. The method according to Option 1, wherein the resistance measured by the anode ohmic resistor is modified by Butler-Volmer simulation.

[0032] Option 7. The method according to Option 1, wherein the operation further includes:

[0033] Measure the resistance of at least one cathode resistor-capacitor pair; and

[0034] The capacitor of at least one cathode resistor-capacitor pair is dynamically updated based on the measured resistance and time constant.

[0035] Option 8. The method according to Option 1, wherein the operation further includes:

[0036] Measure the resistance of at least one anode resistor-capacitor pair; and

[0037] The capacitor of at least one anode resistor-capacitor pair is dynamically updated based on the measured resistance and time constant.

[0038] Option 9. The method according to Option 1, wherein the operation further includes:

[0039] Receive the separator overpotential measured by the separator ECM of the battery cell; and

[0040] A virtual reference electrode for the battery cell is generated based on the separator overpotential and the anode potential.

[0041] Option 10. The method according to Option 1, wherein the battery cell supplies power to the vehicle.

[0042] Option 11. A system comprising:

[0043] Data processing hardware; and

[0044] Memory hardware communicating with the data processing hardware, the memory hardware storing instructions, which, when executed on the data processing hardware, cause the data processing hardware to perform operations, including:

[0045] Receive the cathode voltage response predicted by the cathode equivalent circuit model (ECM) of the battery cell, the cathode ECM including the cathode open circuit voltage (OCV), the cathode ohmic resistor and at least one cathode resistor-capacitor pair;

[0046] Receive the anode voltage response predicted by the anode ECM of the battery cell, the anode ECM including the anode OCV, the anode ohmic resistor and at least one anode resistor-capacitor pair;

[0047] Determine the cathode resistance voltage drop across the cathode ohmic resistor;

[0048] Determine the voltage drop across the anode resistor of the anode ohmic resistor;

[0049] Determine the cathode electrode voltage drop across at least one cathode resistor-capacitor pair;

[0050] Determine the anode voltage drop across at least one anode resistor-capacitor pair;

[0051] Determine whether the cathode potential of the battery cell exceeds the cathode potential threshold based on the cathode resistance voltage drop and the cathode electrode voltage drop;

[0052] Determining whether the anode potential of the battery cell has dropped below the anode potential threshold based on the anode resistance voltage drop and the anode electrode voltage drop; and

[0053] When one or more cathode potentials of the battery cell exceed the cathode threshold potential, or when the anode potential of the battery cell drops below the anode potential threshold, the charging current supplied to the battery cell is modified.

[0054] Option 12. The system according to Option 11, wherein the operation further includes:

[0055] Determine the cathode state and the anode state of lithiation;

[0056] Modified lithiation anode state is generated based on the equilibrium potential of the battery cell; and

[0057] The cathode state of lithiation is modified based on the equilibrium potential of the battery cell.

[0058] Option 13. The system according to Option 12, wherein determining whether the cathode potential of the battery cell exceeds the cathode potential threshold is further based on the modified lithiation cathode state.

[0059] Option 14. The system according to Option 12, wherein determining whether the anode potential of the battery cell has dropped below the anode potential threshold is further based on the modified lithiation anode state.

[0060] Option 15. The system according to Option 11, wherein the resistance measured by the cathode ohmic resistor is modified by Butler-Volmer simulation.

[0061] Option 16. The system according to Option 11, wherein the resistance measured by the anode ohmic resistor is modified by Butler-Volmer simulation.

[0062] Option 17. The system according to Option 11, wherein the operation further includes:

[0063] Measure the resistance of at least one cathode resistor-capacitor pair; and

[0064] The capacitor of at least one cathode resistor-capacitor pair is dynamically updated based on the measured resistance and time constant.

[0065] Option 18. The system according to Option 11, wherein the operation further includes:

[0066] Measure the resistance of at least one anode resistor-capacitor pair; and

[0067] The capacitor of at least one anode resistor-capacitor pair is dynamically updated based on the measured resistance and time constant.

[0068] Option 19. The system according to Option 11, wherein the operation further includes:

[0069] Receive the separator overpotential measured by the separator ECM of the battery cell; and

[0070] A virtual reference electrode for the battery cell is generated based on the separator overpotential and the anode potential.

[0071] Option 20. The system according to Option 11, wherein the battery unit supplies power to the vehicle.

[0072] Details of one or more implementations of this disclosure are set forth in the accompanying drawings and the following description. Other aspects, features, and advantages will become clear from the specification, drawings, and claims. Attached Figure Description

[0073] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure.

[0074] Figure 1 This is a schematic diagram of an example system using fast charging control with a modified equivalent circuit model.

[0075] Figure 2 yes Figure 1 A schematic diagram of an example component of the system.

[0076] Figure 3 It is used for Figure 1 The flowchart of the fast charging control model of the system.

[0077] Figure 4 This is a flowchart of an example operational arrangement for a fast charging control method with a modified equivalent circuit model.

[0078] Throughout the accompanying drawings, the corresponding reference numerals indicate the relevant parts. Detailed Implementation

[0079] The example configuration will now be described more fully with reference to the accompanying drawings. The example configuration is provided so that this disclosure will be thorough and will fully communicate the scope of this disclosure to those skilled in the art. Specific details, such as examples of specific components, devices, and methods, are set forth to provide a thorough understanding of the configuration of this disclosure. It will be apparent to those skilled in the art that specific details are not required, the example configuration may be embodied in many different forms, and the specific details and example configuration should not be construed as limiting the scope of this disclosure.

[0080] The terminology used herein is for the purpose of describing specific exemplary configurations only and is not intended to be limiting. As used herein, the singular articles “a,” “an,” and “the” may also be intended to include plural forms unless the context clearly indicates otherwise. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore specify the presence of features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof. The method steps, processes, and operations described herein should not be construed as requiring them to be performed in the specific order discussed or illustrated, unless specifically identified as such. Additional or alternative steps may be employed.

[0081] When an element or layer is referred to as "on another element or layer," "joined to," "connected to," "attached to," or "coupled to" another element or layer, it may be directly on, joined to, connected to, attached to, or coupled to the other element or layer, or there may be intermediate elements or layers present. Conversely, when an element is referred to as "directly on another element or layer," "directly joined to," "directly connected to," "directly attached to," or "directly coupled to" another element or layer, there may be no intermediate elements or layers present. Other terms used to describe relationships between elements should be interpreted in a similar manner (e.g., "between" versus "directly between," "adjacent" versus "directly adjacent," etc.). As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0082] The terms “first,” “second,” “third,” etc., may be used herein to describe various elements, components, regions, layers, and / or sections. These elements, components, regions, layers, and / or sections should not be limited by these terms. These terms are used only to distinguish one element, component, region, layer, or section from another. Terms such as “first,” “second,” and other numerical terms do not imply order or sequence unless the context clearly indicates otherwise. Therefore, the first element, component, region, layer, or section discussed below may be referred to as the second element, component, region, layer, or section without departing from the teachings of the example configuration.

[0083] In this application, including the following definitions, the term "module" may be replaced by the term "circuit". The term "module" may refer to or include, in part, or all of the following: application-specific integrated circuit (ASIC); digital, analog, or mixed-signal analog / digital discrete circuit; digital, analog, or mixed-signal analog / digital integrated circuit; combinational logic circuit; field-programmable gate array (FPGA); processor (shared, dedicated, or grouped) for executing code; memory (shared, dedicated, or grouped) for storing code executed by the processor; other suitable hardware components that provide the aforementioned functionality; or combinations of some or all of the above, such as in a system-on-a-chip.

[0084] The term "code" as used above can include software, firmware, and / or microcode, and can refer to programs, routines, functions, classes, and / or objects. The term "shared processor" includes a single processor that executes some or all of the code from multiple modules. The term "group processor" includes processors combined with additional processors that execute some or all of the code from one or more modules. The term "shared memory" includes a single memory that stores some or all of the code from multiple modules. The term "group memory" includes memory combined with additional memory that stores some or all of the code from one or more modules. The term "memory" can be a subset of the term "computer-readable medium." The term "computer-readable medium" does not include transient electrical and electromagnetic signals propagating through the medium, and therefore can be considered tangible and non-transient memory. Non-limiting examples of non-transient memory include tangible computer-readable media, including non-volatile memory, magnetic storage devices, and optical storage devices.

[0085] The apparatus and methods described in this application may be implemented, in whole or in part, by one or more computer programs executed by one or more processors. The computer program includes processor-executable instructions stored on at least one non-transitory tangible computer-readable medium. The computer program may also include and / or depend on stored data.

[0086] A software application (i.e., a software resource) can refer to computer software that enables a computing device to perform tasks. In some examples, a software application may be referred to as an "application," "app," or "program." Example applications include, but are not limited to, system diagnostic applications, system management applications, system maintenance applications, word processing applications, spreadsheet applications, messaging applications, media streaming applications, social networking applications, and game applications.

[0087] Non-transitory memory can be a physical device used to store programs (e.g., instruction sequences) or data (e.g., program state information) on a temporary or permanent basis for use by a computing device. Non-transitory memory can be volatile and / or non-volatile addressable semiconductor memory. Examples of non-volatile memory include, but are not limited to, flash memory and read-only memory (ROM) / programmable read-only memory (PROM) / erasable programmable read-only memory (EPROM) / electrically erasable programmable read-only memory (EEPROM) (e.g., commonly used in firmware, such as boot programs). Examples of volatile memory include, but are not limited to, random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), phase-change memory (PCM), and magnetic disks or magnetic tapes.

[0088] These computer programs (also referred to as programs, software, software applications, or code) include machine instructions for a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages ​​and / or assembly / machine languages. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, non-transitory computer-readable medium, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) used to provide machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term “machine-readable signal” refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0089] Various implementations of the systems and techniques described herein can be implemented in digital electronic and / or optical circuit systems, integrated circuit systems, specially designed ASICs (Application-Specific Integrated Circuits), computer hardware, firmware, software, and / or combinations thereof. These different implementations can include implementations in one or more computer programs executable and / or interpretable on a programmable system, which includes at least one programmable processor, at least one input device, and at least one output device. The at least one programmable processor can be dedicated or general-purpose and is coupled to receive data and instructions from and transfer data and instructions to the storage system.

[0090] The processes and logical flows described in this specification can be executed by one or more programmable processors, also known as data processing hardware, which execute one or more computer programs to perform functions by manipulating input data and generating output. The processes and logical flows can also be executed by a dedicated logic circuit system, such as an FPGA (Field-Programmable Gate Array) or an ASIC (Application-Specific Integrated Circuit). By way of example, processors suitable for executing computer programs include both general-purpose and dedicated microprocessors, as well as any one or more processors of any kind of digital computer. Typically, the processor receives instructions and data from read-only memory or random access memory, or both. The basic elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include, or be operatively coupled to, one or more mass storage devices for storing data, such as a magnetic disk, magneto-optical disk, or optical disk, to receive data from or transfer data to, or both of, these mass storage devices. However, a computer does not need to have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including, by example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks or removable disks; magneto-optical disks; and CD-ROMs and DVD-ROMs. The processor and memory may be supplemented by or incorporated into a dedicated logic circuit system.

[0091] To provide interaction with the user, one or more aspects of this disclosure can be implemented on a computer having: a display device for displaying information to the user—such as a CRT (cathode ray tube), LCD (liquid crystal display) monitor, or touchscreen—and optional keyboard and pointing devices—such as a mouse or trackball, through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback, such as visual, auditory, or tactile feedback; and input from the user can be received in any form, including sound, speech, or tactile input. Furthermore, the computer can interact with the user by sending documents to and receiving documents from the device used by the user; for example, by sending a webpage to a web browser on the user's client device in response to a request received from a web browser.

[0092] refer to Figure 1In some implementations, system 100 includes a vehicle 10, a charging station 20 (e.g., an electric vehicle (EV) charging station 20), and / or a remote system 60 communicating with each other via a network 40. As shown, vehicle 10 connects to charging station 20 when charging station 20 supplies charging current 22 to battery 16 of vehicle 10. Vehicle 10 and / or remote system 60 execute a fast charging control system 200 including an equivalent circuit model (ECM) system 202. Figure 2 The Equivalent Circuit Model (ECM) system 202 is configured to predict the voltage responses 212C, 212S, 212A of one or more ECMs 210C, 210S, 210A, and to modify the charging current 22 currently supplied to the battery cell 16 of the vehicle 10 when one or more voltage responses 212 indicate that the battery cell 16 is at risk of overheating, lithium plating, and / or violation of operating voltage limits. Advantageously, because the individual voltage responses 212C, 212S, 212A are measurable / predictable, the terminal voltage response of the battery cell 16 can also be predicted. By knowing the anode potential of the battery cell 16, the fast charging control system 200 can control the charging current 22 to a minimum voltage to limit lithium plating. Similarly, by knowing the cathode potential of the battery cell 16, the fast charging control system 200 can control the charging current 22 to a maximum voltage to avoid cathode material degradation or gas generation.

[0093] In the example shown, the fast charging control system 200 is implemented within the vehicle 10. However, the fast charging control system 200 can be implemented on other computing devices (e.g., computing devices communicating with the vehicle 10), which are, without limitation, such as smartphones, tablets, smart displays, desktop / laptop computers, smartwatches, smart appliances, or smart glasses / earphones. The vehicle 10 includes data processing hardware 12 and memory hardware 14 storing instructions that, when executed on the data processing hardware 12, cause the data processing hardware 14 to perform operations. The vehicle 10 further includes battery cells 16 (i.e., a group of cells in a battery pack) that supply power to drive the vehicle 10. The battery cells 16 may include a cathode, an anode, and a separator between the cathode and the anode.

[0094] Network 40 may include a wireless local area network (WLAN) that facilitates communication and interoperability between vehicle 10 and remote systems 60 within the vehicle 10 environment. Therefore, network 40 may include wireless fidelity. (e.g., IEEE 802.11), low-rate wireless personal area networks (e.g., IEEE 802.15.4), WiMAX, 3G, 4G, LTE, 5G, digital subscriber line (DSL), Bluetooth, near field communication (NFC), or any other wireless standard, or Ethernet (e.g., IEEE 802.3). System 100 may additionally include one or more access points (APs) (not shown) configured to facilitate wireless communication between vehicle 10 and remote system 60.

[0095] The remote system 60 (e.g., a server, cloud computing environment) also includes data processing hardware 62 and memory hardware 64 for storing instructions, which, when executed on the data processing hardware 62, cause the data processing hardware 62 to perform operations. In some examples, the execution of the fast charging control system 200 is shared across the vehicle 10 and the remote system 60. See below for reference. Figure 2 and 3 In more detail, the fast charging control system 200 implemented on the vehicle 10 and / or the remote system 60 executes the ECM system 202 and the charging control model 300. Here, the voltage response 212 predicted by the ECM system 202 can be used by the charging control model 300 to modify the charging current 22 supplied to the battery cell 16 of the vehicle.

[0096] Specific reference Figure 2 The ECM system 202 may include a cathode ECM 210C, an anode ECM 210A, and a separator ECM 210S. As shown, the cathode ECM 210C includes a cathode open-circuit voltage (OCV) 214 (also referred to as cathode 214), a cathode ohmic resistor 220C, and at least one cathode resistor-capacitor pair 222. C 222 C a-222 C Similarly, the anode ECM 210A includes an anode OCV 218 (also known as anode 218), an anode ohmic resistor 220A, and at least one anode resistor-capacitor pair 222. A 222 A a-222 A n. The separator ECM 210S may include a separator electrode OCV 216, a separator ohmic resistor 220S, and at least one separator resistor-capacitor pair 222. S 222 S a-222 S n. In some examples, the cathode ECM 210C is a resistor-capacitor pair 222. CThe four-parameter (4P) ECM, the separator ECM 210S, is a 222 resistor-capacitor pair. A a、222 A b is a six-parameter (6P) ECM, and the anode ECM 210A is a resistor-capacitor pair 222. A The four-parameter (4P) ECM is used. However, it should be understood that each corresponding ECM 210 of the ECM system 202 may include additional or fewer resistor-capacitor pairs 222 to modify the parameters of the corresponding ECM 210 (e.g., 4P, 6P, 8P, 10P, etc.). Furthermore, each of the ECMs 210C, 210A can operate independently of each other (i.e., decoupled).

[0097] In some cases, the cathode is OCV 214, the cathode ohmic resistor is 220C, and at least one cathode resistor-capacitor pair is 222. C Anode OCV 218, anode ohmic resistor 220A and at least one anode resistor-capacitor pair 222 A The parameters for each of these are defined by an individual lookup table. In other cases, the cathode is OCV 214, the cathode ohmic resistor is 220C, and at least one cathode resistor-capacitor pair is 222. C Anode OCV 218, Anode Ohmic Resistor 220 A and at least one anode resistor-capacitor pair 222 A Each of the parameters is defined by an algebraic equation. In any case, these parameters can be looked up and calculated as a function of one or more of temperature, state of charge / lithiation, applied current, or the direction of applied current (i.e., delithiation relative to lithiation; charge relative to current).

[0098] In some cases, the ohmic resistance measured by one or more of the cathode ohmic resistor 220C or anode ohmic resistor 220A is modified by Butler-Volmer simulation. Here, Butler-Volmer simulation is applied such that the ohmic resistance as a function of the current, which follows the curve shape of the Butler-Volmer kinetic equations, is nonlinear. It is worth noting that the standard ohmic resistance function typically does not capture the kinetic response and is instead constant with respect to the applied current. This application of the shape function, compared to the constant lookup function traditionally used to capture the relationship between the state of lithiation and the equilibrium potential of cell 16, can be applied to further consider the effect of diffusion on the equilibrium potential of cell 16.

[0099] Continue to refer to Figure 2The ECM system 202 can generate a voltage response 212C predicted by the cathode ECM 210C, a voltage response 212A predicted by the anode ECM 210A, and a voltage response 212S predicted by the cathode ECM 210S as outputs. The charging control model 300 receives the predicted voltage responses 212C, 212A, and 212S as inputs and generates a modified charging current 22M for the battery cell 16 as output to protect the battery cell 16 by avoiding lithium plating and overcharging of the cathode OCV 214.

[0100] refer to Figure 3 The flowchart of the charging control model 300 is shown. The flowchart of the charging control model 300 can be executed at each forward time step t as the charging current 22 is applied to the battery cell 16 of the vehicle 10. In operation 310, the charging control model 300 calculates the cathode resistor voltage drop 312C across the cathode ohmic resistor 220C, and the anode resistor voltage drop 312 across the anode ohmic resistor 220A. The charging control model 300 can calculate the corresponding resistor voltage drops 312C and 312A by first calculating the ohmic resistance R0 measured by the corresponding ohmic resistors 220C and 220A, and applying the principles of Ohm's law.

[0101] Here, the ohmic resistance R0 measured by one or more of the cathode ohmic resistor 220C or anode ohmic resistor 220A is modified by Butler-Volmer simulation. Butler-Volmer simulation can be applied such that the ohmic resistance R0 is nonlinear as a function of the current with a curve shape following the Butler-Volmer kinetic equations. It is noteworthy that the standard ohmic resistance function typically does not capture the kinetic response and is instead constant with respect to the applied current. This application of the shape function, compared to the constant lookup function traditionally used to obtain the relationship between the state of lithiation and the equilibrium potential of cell 16, can be applied to further consider the effect of diffusion on the equilibrium potential of cell 16.

[0102] Here, the ohmic resistance R0 of the cathode ohmic resistor 220C 阴极 And the ohm resistor R0 of the anode ohm resistor 220A 阳极 They can be defined as follows:

[0103]

[0104] and

[0105]

[0106] Where V indicates voltage, I applied Indicates the applied current, and I referenceThe reference current is indicated. In addition, a indicates the nonlinearity factor, and μ indicates the ratio between linearity and total resistance, where the behavior is linear when mu equals one (1) and nonlinear when mu equals zero (0).

[0107] Subsequently, in operation 310, the charging control model 300 can apply Ohm's law to the current (denoted as i) passing through in the instantaneous time step t. app The ohmic resistance R0 of the cathode and R0 calculated under the following conditions. 阳极 The cathode resistance voltage drop 312C across the cathode ohmic resistor 220C and the anode resistance voltage drop 312A across the anode ohmic resistor 220A are determined as follows:

[0108] V drop_ROcathode =i app *RO cathode (3), and

[0109] V drop_ROanode =i app *RO anode (4).

[0110] In operation 314, charging control model 300 determines the cross-section of at least one cathode resistor-capacitor pair 222. C The cathode voltage drop above is 316C, and across at least one anode resistor-capacitor pair is 222. A The anode voltage drop is 316A. As should be understood, the charging control model 300 determines a corresponding voltage drop 316A for each resistor-capacitor pair 222 in system 100. For example, if the cathode ECM 210C comprises a single resistor-capacitor pair 222C, the charging control model 300 determines a single cathode voltage drop 316C across the single resistor-capacitor pair 222C. Similarly, if the anode ECM 210A comprises two resistor-capacitor pairs 222... A a、222 A b, then the charging control model 300 can be two resistor-capacitor pairs 222 A a、222 A Each of the values ​​in b determines the corresponding anode voltage drops 316A1 and 316A2. The current i and voltage drop 316 across each resistor-capacitor pair 222 can be captured using ordinary differential equations, as follows:

[0111]

[0112] Where i RC The voltage drop across a resistor-capacitor pair of 222 is 316 (also known as V). RCV represents the voltage across the resistor-capacitor pair 22, R represents the resistance of the resistor-capacitor pair 222, and time is a constant. It is worth noting that while the parameters of the RC pair are generally known using a lookup table, the charging control model 300 can dynamically calculate the capacitor parameters and / or update the capacitor of the resistor-capacitor pair 222 based on the measured resistance R and the time constant.

[0113] In operations 318C and 318A, the charging control model 300 calculates the corresponding total voltage drops 320C and 320A. Specifically, in operation 318C, the charging control model 300 determines the total cathode voltage drop 320C of the cathode ECM 210C based on the cathode resistor voltage drop 312C and the cathode electrode voltage drop 316C. Simultaneously, in operation 318C, the charging control model 300 determines the total anode voltage drop 320A of the anode ECM 210A based on the anode resistor voltage drop 312A and the anode voltage drop 316A. Here, the total voltage drops 320C and 320A can be calculated separately as follows:

[0114] V drop_cathode =V drop_ROcathode +V R1C1_cathode (6), and

[0115] V drop_anode =V drop_ROanode +V R1C1_anode (7).

[0116] In operation 322C, the charging control model 300 calculates the current cathode state of lithiation (SoL) 324C. Similarly, in operation 322A, the charging control model 300 calculates the current anode SoL 324A. Here, the charging control model 300 uses battery balance parameters to compare the cathode SoL 324C and anode SoL 324A with the battery state of charge (i.e., τ) of each of cathodes 214 and anodes 218. cell The association is as follows.

[0117] x A =[x A，charged -x A，discharged ]τ cell +x A，discharged (8), and

[0118] x C =[x C，discharged -x C，charged ][1-τ cell ]+x C，charged (9).

[0119] During the initialization of the charging control model 300, the stoichiometric parameters used to determine the cell 16 of the cathode SoL324C are defined as x. C And the anode SoL 324A is defined as x A It can be defined as follows: x A，charged Indicates the fraction of anode lithiation at maximum cell state of charge (SoC), x A，discharged Indicates the fraction of anode lithium-ion in the smallest battery cell SoC, x C，charged Indicates the cathode lithiation fraction under the largest battery cell SoC, and x C，discharged Indicates the cathode lithiation fraction under the smallest battery cell SoC.

[0120] In operation 326C, the charging control model 300 generates a modified cathode SoL328C based on the equilibrium potential U of battery cell 16. Specifically, the charging control model 300 can define the relationship between the equilibrium potential U and the cathode SoL324C to modify the cathode SoL324C. Similarly, in operation 326A, the charging control model generates a modified anode SoL328A based on the equilibrium potential U. Here, the corresponding modifications to SoL328C and 328A can be calculated in real time, as follows:

[0121] U cathode =f(SoL cathode +SF)(10), and

[0122] U anode =f(SoL anode +SF)(11),

[0123] Among them U cathode The cathode SoL328C, U is marked as modified. anode The modified anode SoL 328A, SoL cathode The cathode is labeled SoL324C, SoL anode The anode is labeled SoL 324A, and SF indicates the offset function of the battery cell 16 of vehicle 10.

[0124] In operation 330C, the charging control model 300 receives the modified cathode SoL 328C and the previously calculated total cathode voltage drop 320C, and calculates the cathode potential 332C (i.e., V) of the battery cell 316. cathode ),as follows:

[0125] V cathode =V drop_cathode +U cathode (12).

[0126] Similarly, in operation 330A, the charging control model 300 receives the modified anode voltage drop 328A and the previously calculated total anode voltage drop 320A, and calculates the anode potential 332A of the battery cell 316 as follows:

[0127] V anode =V drop_anode +U anode (13).

[0128] In operation 334, the charging control model 300 determines whether the cathode potential 332C exceeds a cathode potential threshold. For example, the charging control model 300 may define the cathode potential threshold as the maximum cathode potential that avoids damage to the cathode active material in cell 16. This damage may include cracking or site loss due to metal migration occupying lithium intercalation sites caused by structural collapse. If the cathode potential 332C does not exceed the cathode potential threshold, the charging control model 300 may increment forward in the next time step. However, if the cathode potential 332C does exceed the cathode potential threshold, the charging control model 300 may iterate over the current flowing between cathode 314 and anode 318 (i.e., i...). app The sweeping continues until the feedforward prediction of the cathode potential 332C does not exceed the cathode potential threshold.

[0129] In operation 336, the charging control model 300 determines whether the anode potential 332A has dropped below an anode potential threshold. For example, the charging control model 300 may define an anode potential threshold to avoid lithium plating. If the anode potential 332A is above the anode potential threshold, the charging control model 300 may increment forward in the next time step. Conversely, if the anode potential 332A drops below the anode potential threshold, the charging current model 300 may iteratively increment the current (i.e., i) passing through it. app The sweep continues until the feedforward prediction of the anode potential 332A is higher than the anode potential threshold. In some implementations, the charging control model 300 receives the separator overpotential measured by the separator ECM210S and generates a virtual reference electrode for the battery cell 16 based on the separator overpotential and the calculated anode potential 332A.

[0130] In operation 338, when the cathode potential 332C of battery cell 16 exceeds the cathode threshold potential and the anode potential 332A of battery cell 16 drops below one or both of the anode potential threshold, the charging control model 300 modifies the charging current 22 supplied to battery cell 16. Here, the modified charging current 22M can be the current i passing through operations 334 and 336. app The corresponding current i is calculated during the iterative sweep. appThe minimum value. This minimum value may be defined by one or more of the following: architectural limits (e.g., bus maximum), battery hard limits, charger limits, thermal runaway limits, and shall not exceed the cathode potential threshold or drop below the anode potential threshold.

[0131] Subsequently, the charging control model 300 can transmit instructions to the vehicle 10 and / or the charging station to update the charging current 22 applied to the battery cell to a modified charging current 22M. In operation 340, the charging control model 300 determines whether charging of the battery cell 16 is complete (e.g., at or above 80% SoC). If charging of the battery cell 16 is not complete, the charging control model 300 can increment the next time step to continue monitoring the state of the battery cell 16. Conversely, if charging of the battery cell 16 is complete, the charging control model 300 can terminate / cut off the charging current 22 to the battery cell 16.

[0132] Figure 4 A flowchart illustrating an example operational arrangement for a fast charging control method 400 using an equivalent circuit model is shown. See also... Figure 1-3 To describe method 400. Data processing hardware (e.g., Figure 1 Data processing hardware 12, 62) can execute data stored in memory hardware (e.g., Figure 1 The instructions on the memory hardware (14, 64) are configured to perform an example arrangement for the operation of method 400. In operation 402, method 400 includes receiving a cathode voltage response 212C predicted by the cathode equivalent circuit model (ECM) 210C of the battery cell 16. Here, the cathode ECM 210C includes a cathode OCV 214, a cathode ohmic resistor 220C, and at least one cathode resistor-capacitor (also referred to as RC) pair 222. C 222 C a-222 C n.

[0133] In operation 404, method 400 further includes receiving an anode voltage response 212A predicted by the anode ECM 210A of the battery cell 16. Here, the anode ECM 210A includes an anode OCV 218, an anode ohmic resistor 220A, and at least one anode resistor-capacitor pair 222. A 222 A a-222 A n. Method 400 further includes, in operation 406, determining a cathode resistance voltage drop 312C across the cathode ohmic resistor 220C. In operation 408, method 400 further includes determining an anode resistance voltage drop 312A across the anode ohmic resistor 220A.

[0134] Method 400 also includes, in operation 410, determining across at least one cathode resistor-capacitor pair 222 C The cathode electrode voltage drop above is 316C. In operation 412, operation 400 also includes determining the voltage across at least one anode resistor-capacitor pair 222. A The anode voltage drop is 316A. In operation 414, method 400 also includes determining whether the cathode potential 332C of the battery cell 16 exceeds the cathode potential threshold based on the cathode resistance voltage drop 312C and the cathode voltage drop 316C.

[0135] In operation 416, method 400 further includes determining whether the anode potential 332A of the battery cell has dropped below an anode potential threshold based on the anode resistance voltage drop 312A and the anode voltage drop 316A. When one or more of the cathode potentials 332C exceed the cathode threshold, or the anode potential 332A drops below the anode threshold, method 400 further includes, in operation 418, modifying the charging current 22 supplied to the battery cell 16.

[0136] These operations also include determining the cathode resistance voltage drop across the cathode ohmic resistor, determining the anode resistance voltage drop across the anode ohmic resistor, determining the cathode electrode voltage drop across at least one cathode resistor-capacitor pair, and determining the anode electrode voltage drop across at least one anode resistor-capacitor pair. The operations further include determining whether the cathode potential of the battery cell exceeds a cathode potential threshold based on the cathode resistance voltage drop and the cathode electrode voltage drop, and determining whether the anode potential of the battery cell drops below an anode potential threshold based on the anode resistance voltage drop and the anode electrode voltage drop. When one or more cathode potentials of the battery cell exceed the cathode threshold potential, or when the anode potential of the battery cell drops below the anode potential threshold, the operations also include modifying the charging current supplied to the battery cell.

[0137] Several implementations have been described. However, it will be understood that various modifications can be made without departing from the spirit and scope of this disclosure. Therefore, other implementations are also within the scope of the following claims.

[0138] The foregoing description has been provided for purposes of illustration and description. It is not intended to be exhaustive or limiting of this disclosure. Individual elements or features of a particular configuration are generally not limited to that particular configuration, but where applicable, they are interchangeable and can be used in the selected configuration, even if not specifically shown or described. This can also be varied in many ways. Such variations should not be considered as departing from this disclosure, and all such modifications are intended to be included within the scope of this disclosure.

Claims

1. A computer-implemented method executed on data processing hardware, the method causing the data processing hardware to perform operations, the operations including: Receive the cathode voltage response measured by the cathode equivalent circuit model (ECM) of the battery cell, the cathode ECM including a cathode, a cathode ohmic resistor and at least one cathode resistor-capacitor pair; Receive the anode voltage response measured by the anode ECM of the battery cell, the anode ECM including an anode, an anode ohmic resistor and at least one anode resistor-capacitor pair; Determine the cathode resistance voltage drop across the cathode ohmic resistor; Determine the voltage drop across the anode resistor of the anode ohmic resistor; Determine the cathode electrode voltage drop across at least one cathode resistor-capacitor pair; Determine the anode voltage drop across at least one anode resistor-capacitor pair; Determine whether the cathode potential of the battery cell exceeds the cathode potential threshold based on the cathode resistance voltage drop and the cathode electrode voltage drop; Determine whether the anode potential of the battery cell has dropped below the anode potential threshold based on the anode resistance voltage drop and the anode electrode voltage drop; and When one or more cathode potentials of the battery cell exceed the cathode threshold potential, or when the anode potential of the battery cell drops below the anode potential threshold, the charging current supplied to the battery cell is modified.

2. The method according to claim 1, wherein, The operation further includes: Determine the cathode state and the anode state of lithiation; Modified lithiation anode state is generated based on the equilibrium potential of the battery cell; and The cathode state of lithiation is modified based on the equilibrium potential of the battery cell.

3. The method according to claim 2, wherein, Determining whether the cathode potential of the battery cell exceeds the cathode potential threshold is further based on the modified cathode state of lithiation.

4. The method according to claim 2, wherein, Determining whether the anode potential of the battery cell has dropped below the anode potential threshold is further based on the modified anode state of lithiation.

5. The method according to claim 1, wherein, The resistance measured by the cathode ohm resistor was modified by the Butler-Volmer simulation.

6. The method according to claim 1, wherein, The resistance measured by the anode ohm resistor was modified by the Butler-Volmer simulation.

7. The method according to claim 1, wherein, The operation further includes: Measure the resistance of at least one cathode resistor-capacitor pair; and The capacitor of at least one cathode resistor-capacitor pair is dynamically updated based on the measured resistance and time constant.

8. The method according to claim 1, wherein, The operation further includes: Measure the resistance of at least one anode resistor-capacitor pair; and The capacitor of at least one anode resistor-capacitor pair is dynamically updated based on the measured resistance and time constant.

9. The method according to claim 1, wherein, The operation further includes: Receive the separator overpotential measured by the separator ECM of the battery cell; and A virtual reference electrode for the battery cell is generated based on the separator overpotential and the anode potential.

10. The method according to claim 1, wherein, The battery unit supplies power to the vehicle.

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