Battery state estimation using an equivalent constant current model of overpotential

Abstract

The present invention relates to battery state estimation using an equivalent constant current model of overpotential. A system includes a state of charge (SOC) calculation module configured to calculate an SOC of a battery cell based on a measured current of the battery cell, and an overpotential calculation module configured to receive the measured current and output a lag current based on the measured current and a corresponding time constant, output a weighted measured current and a weighted lag current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is one, calculate an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted lag current, and calculate an overpotential of the battery cell based on the equivalent constant current. The system is configured to output a predicted voltage of the battery cell based on the calculated SOC and the calculated overpotential of the battery cell.

Description

[0001] INTRODUCTION

[0002] The information provided in this section is for the purpose of generally presenting the context of the disclosure. As such, the description set forth in this section is not to be taken as an admission that any of the descriptions presented constitute prior art to the currently claimed disclosure nor is it necessarily a complete exposition of the background of the current application. TECHNICAL FIELD

[0003] The present disclosure relates to vehicles, and more particularly, to battery systems of vehicles. BACKGROUND

[0004] Some types of vehicles include only internal combustion engines that generate propulsion torque. Pure electric vehicles include a battery system and electric motors. Hybrid vehicles include internal combustion engines and one or more electric motors, and can include a battery system. The battery system includes one or more batteries or battery modules. Each battery module includes one or more battery cells. SUMMARY

[0005] A system includes a state of charge (SOC) calculation module configured to calculate an SOC of a battery cell based on a measured current of the battery cell, and an overpotential calculation module configured to receive the measured current and output a lag current based on the measured current and a corresponding time constant, output a weighted measured current and a weighted lag current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is one, calculate an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted lag current, and calculate an overpotential of the battery cell based on the equivalent constant current. The system is configured to output a predicted voltage of the battery cell based on the calculated SOC and the calculated overpotential of the battery cell.

[0006] In other features, the overpotential calculation module includes a plurality of lag current modules configured to calculate the lag current.

[0007] In other features, the lag current module corresponds to a low pass filter.

[0008] In other features, the weighting factors are a function of the SOC and a temperature of the battery cell.

[0009] In other features, the equivalent constant current is a sum of the weighted current and the weighted lag current.

[0010] In other features, the overpotential calculation module is configured to calculate the overpotential further based on the SOC and a temperature of the battery cell.

[0011] In other features, the overpotential calculation module is configured to calculate the overpotential using a lookup table. In other features, the overpotential calculation module is configured to calculate the overpotential using a lookup table.

[0012] In other features, the predicted voltage is a sum of the open-circuit voltage and the overpotential.

[0013] In other features, the predicted voltage is a sum of the open-circuit voltage, the overpotential, and a hysteresis voltage of the battery cell.

[0014] In other features, the system further includes a hysteresis module configured to calculate a hysteresis voltage of the battery cell.

[0015] A method includes calculating a SOC of a battery cell based on a measured current of the battery cell; receiving the measured current and outputting a lag current based on the measured current and a corresponding time constant; outputting a weighted measured current and a weighted lag current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is one; calculating an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted lag current; calculating an overpotential of the battery cell based on the equivalent constant current; and outputting a predicted voltage of the battery cell based on the calculated SOC of the battery cell and the calculated overpotential of the battery cell.

[0016] In other features, the method further includes outputting the lag current using a low-pass filter.

[0017] In other features, the weighting factors are a function of the SOC and a temperature of the battery cell.

[0018] In other features, the method further includes summing the weighted current and the weighted lag current to calculate the equivalent constant current.

[0019] In other features, the method further includes calculating the overpotential further based on the SOC and a temperature of the battery cell.

[0020] In other features, the method further includes calculating the overpotential using a lookup table.

[0021] In other features, the predicted voltage is a sum of the open-circuit voltage and the overpotential.

[0022] In other features, the predicted voltage is a sum of the open-circuit voltage, the overpotential, and a hysteresis voltage of the battery cell.

[0023] The present invention provides the following technical solutions.

[0024] Technical Solution 1. A system comprising:

[0025] a state-of-charge (SOC) calculation module configured to calculate a SOC of a battery cell based on a measured current of the battery cell; and

[0026] an overpotential calculation module configured to

[0027] receiving the measured current and outputting a lag current based on the measured current and a corresponding time constant,

[0028] outputting a weighted measured current and a weighted lag current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is 1,

[0029] calculating an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted lag current, and

[0030] calculating an overpotential of the battery cell based on the equivalent constant current,

[0031] wherein the system is configured to output a predicted voltage of the battery cell based on the calculated SOC and the calculated overpotential of the battery cell.

[0032] Technical solution 2. The system of technical solution 1, wherein the overpotential calculation module comprises a plurality of lag current modules configured to calculate the lag current.

[0033] Technical solution 3. The system of technical solution 2, wherein the lag current module corresponds to a low-pass filter.

[0034] Technical solution 4. The system of technical solution 1, wherein the weighting factors are functions of the SOC and temperature of the battery cell.

[0035] Technical solution 5. The system of technical solution 1, wherein the equivalent constant current is a sum of the weighted current and the weighted lag current.

[0036] Technical solution 6. The system of technical solution 1, wherein the overpotential calculation module is configured to calculate the overpotential further based on the SOC and temperature of the battery cell.

[0037] Technical solution 7. The system of technical solution 6, wherein the overpotential calculation module is configured to calculate the overpotential using a lookup table.

[0038] Technical solution 8. The system of technical solution 1, wherein the predicted voltage is a sum of an open-circuit voltage and the overpotential.

[0039] Technical solution 9. The system of technical solution 1, wherein the predicted voltage is a sum of an open-circuit voltage, an overpotential, and a hysteresis voltage of the battery cell.

[0040] Technical solution 10. The system of technical solution 9, further comprising a hysteresis module configured to calculate the hysteresis voltage of the battery cell.

[0041] Technical Solution 11. A method comprising:

[0042] calculating a state of charge (SOC) of the battery cell based on a measured current of the battery cell;

[0043] receiving the measured current and outputting a hysteresis current based on the measured current and a corresponding time constant;

[0044] outputting a weighted measured current and a weighted hysteresis current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is one;

[0045] calculating an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted hysteresis current;

[0046] calculating an overpotential of the battery cell based on the equivalent constant current; and

[0047] outputting a predicted voltage of the battery cell based on the calculated SOC and the calculated overpotential of the battery cell.

[0048] Technical Solution 12. The method of Technical Solution 11, further comprising outputting the hysteresis current using a low pass filter.

[0049] Technical Solution 13. The method of Technical Solution 11, wherein the weighting factors are a function of the SOC and temperature of the battery cell.

[0050] Technical Solution 14. The method of Technical Solution 11, further comprising summing the weighted current and the weighted hysteresis current to calculate the equivalent constant current.

[0051] Technical Solution 15. The method of Technical Solution 11, further comprising calculating the overpotential further based on the SOC and temperature of the battery cell.

[0052] Technical Solution 16. The method of Technical Solution 15, further comprising calculating the overpotential using a lookup table.

[0053] Technical Solution 17. The method of Technical Solution 16, wherein the predicted voltage is a sum of an open circuit voltage and the overpotential.

[0054] Technical Solution 18. The method of Technical Solution 11, wherein the predicted voltage is a sum of an open circuit voltage of the battery cell, the overpotential, and a hysteresis voltage.

[0055] Further areas of applicability of the present disclosure will become apparent from the detailed description, the claims and the drawings. The detailed description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0056] The present disclosure will become more fully understood from the detailed description and the accompanying drawings, wherein:

[0057] Figure 1 is a functional block diagram of an example vehicle system according to the present disclosure;

[0058] Figure 2 is a functional block diagram of an example of a battery management system according to the present disclosure;

[0059] Figure 3 is a functional block diagram of an example battery state estimation module according to the present disclosure;

[0060] Figure 4 is a functional block diagram of an example transient dynamics module according to the present disclosure;

[0061] Figure 5 is a step of an example method for calculating an overpotential of a battery cell according to the present disclosure.

[0062] In the drawings, reference numerals can be repeated among the figures for like and / or similar elements. DETAILED DESCRIPTION

[0063] Electric or hybrid electric vehicles typically include a battery system composed of one or more rechargeable batteries or battery modules, each including a plurality of battery cells (e.g., arranged in one or more battery packs). A battery management system (BMS) monitors various parameters of the battery system and controls the operation of the battery system. For example, a battery cell includes a solid or liquid electrolyte arranged between an anode and a cathode of the battery cell. Over the life of the battery, the performance of the battery can degrade due to one or more of electrolyte dry-out, chemical changes in the solid or liquid electrolyte, loss of active lithium, changes in the active materials of the battery cell, etc.

[0064] A battery management system (BMS) can be configured to calculate the state of charge (SOC) of a battery system. For example, the BMS may include a battery state estimation module (or alternatively communicate with a battery state estimation module) configured to estimate or calculate the SOC of the battery system. The battery state estimation module may estimate the SOC based on battery characteristics, including but not limited to measured current, temperature, measured terminal voltage, and voltage predicted by a battery state model. In some examples, the battery state model calculates the predicted voltage based on open-circuit voltage, hysteresis voltage, and overpotential (e.g., the sum of open-circuit voltage, hysteresis voltage, and overpotential).

[0065] In some examples, the overpotential is modeled based on an equivalent circuit such that the total overpotential is the sum of the voltages across the resistor and multiple resistor-capacitor (RC) pairs. In other examples, the equivalent circuit is replaced by a set of low-pass filters, each with a predetermined time constant, whose outputs are the hysteresis form of the measured input current (i.e., hysteresis current). The measured input current and each of the hysteresis currents are multiplied by a resistor to determine the corresponding voltage component, and the corresponding voltage components are summed to calculate the total overpotential. An example model of overpotential based on hysteresis current is described in more detail in U.S. Patent No. 10,928,457, the entire disclosure of which is incorporated herein by reference.

[0066] The battery management system and method according to this disclosure are configured to calculate overpotentials using a model of an equivalent (or "general") constant current. For example, the equivalent constant current is modeled based on each of the measured input current and the hysteresis current. Each of the measured input current and the hysteresis current is multiplied by a corresponding weighting factor and summed to calculate the equivalent constant current (u). cc The sum of the weighting factors is 1. Therefore, the calculated equivalent constant current is an approximation of the measured current that is relatively constant over a predetermined period. For example, the equivalent constant current corresponds to the interpolation between the fully-developed constant current behavior of the battery and the transient behavior of the battery.

[0067] function η( I , x , T This provides the overpotential of the battery at the state of charge x of current I and temperature T when the current I remains relatively constant for a predetermined period of time. Therefore, when current I is replaced by an equivalent constant current, it can be determined based on V. over = η( u cc , x , T Calculate the overpotential V overFor example, the function h( u cc , x , T ) can be implemented as a multi-dimensional lookup table, a mathematical model of the battery or battery cell, etc.

[0068] Although described herein with respect to a vehicle battery (e.g., a rechargeable battery for an electric or hybrid vehicle), the principles of the present disclosure can be applied to batteries used in non-vehicle applications.

[0069] Referring now to Figure 1 , a functional block diagram of an example vehicle system 100 including a battery pack or system 104 according to the present disclosure is shown. The vehicle system 100 can correspond to an autonomous or non-autonomous vehicle. The vehicle can be an electric vehicle (as shown). In other examples, the principles of the present disclosure can be implemented in a hybrid electric vehicle or in a non-vehicle application.

[0070] A vehicle control module 112 controls various operations of the vehicle system 100 (e.g., acceleration, braking, etc.). The vehicle control module 112 can communicate with a transmission control module 116 to, for example, coordinate shifting in the transmission 120. The vehicle control module 112 can communicate with the battery system 104 to, for example, coordinate operation of the electric motor 128. While an example of one electric motor is provided, multiple electric motors can be implemented. The electric motor 128 can be a permanent magnet electric motor, an induction motor, or another suitable type of electric motor that outputs voltage based on back electromotive force (EMF) when free to rotate, such as a direct current (DC) electric motor or a synchronous electric motor. In various implementations, various functions of the vehicle control module 112 and the transmission control module 116 can be integrated into one or more modules.

[0071] Power is applied from the battery system 104 to the electric motor 128 to cause the electric motor 128 to output positive torque. For example, the vehicle control module 112 can include an inverter or inverter module (not shown) to apply power from the battery system 104 to the electric motor 128. The electric motor 128 can output torque to, for example, an input shaft of the transmission 120, an output shaft of the transmission 120, or another component. A clutch 132 can be implemented to couple the electric motor 128 to the transmission 120 and decouple the electric motor 128 from the transmission 120. One or more gear devices can be implemented between an output of the electric motor 128 and an input of the transmission 120 to provide one or more predetermined gear ratios between rotation of the electric motor 128 and rotation of the input of the transmission 120.

[0072] A battery management system (BMS) 136 is configured to control functions of the battery system 104, including but not limited to controlling switching of individual battery modules or cells of the battery system 104, monitoring operational parameters, diagnosing faults, etc. The battery management system 136 can also be configured to communicate with the telematics module 140.

[0073] The battery management system 136 according to the present disclosure is configured to calculate a battery state (e.g., state of charge (SOC) and a corresponding predicted battery voltage) of individual cells of the battery system 104. For example, the battery management system 136 can include (or alternatively be in communication with) a battery state estimation module configured to estimate or calculate a predicted voltage based in part on an overpotential. For example, the battery state estimation module calculates the overpotential based on an equivalent constant current, as described in greater detail below.

[0074] Reference is now made to Figure 2 An example of the battery system 104 and the battery management system 136 is shown in greater detail. The battery system 104 includes a plurality of battery cells 200 and one or more sensors 204 (e.g., voltage, current, temperature, etc.). The battery management system 136 includes a measurement module 208 that coordinates measurements of values from the battery cells and / or battery pack level. Examples of values include temperatures T1, T2,..., voltages V1, V2,..., currents I1, I2,..., reference voltages V ref1 , V ref2 ,..., etc. (e.g., corresponding to respective ones of the battery cells 200).

[0075] A state of health (SOH) module 216 calculates the SOH of the battery system 104 and / or individual ones of the battery cells 200. A schedule and history module 220 schedules testing of the battery cells 200 in response to predetermined events and / or in response to other factors, and stores historical data, at predetermined time periods (e.g., operating time, cycles, etc.). A battery state estimation module 224 determines a state (e.g., SOC) of the battery system 104 and / or the battery cells 200. The battery state estimation module 224 according to the present disclosure uses the SOC and an overpotential based on an equivalent constant current to determine a predicted voltage, as described in greater detail below. Although the battery state estimation module 224 is shown within the battery management system 136, in other examples, the battery state estimation module 224 can be external to the battery management system 136.

[0076] The calibration data storage 228 stores thresholds, parameters, and / or other data related to calibration of the battery system. The thermal management module 232 communicates with a temperature controller 236 to control the temperature of the battery system 104, such as by adjusting coolant flow, air flow, and / or other parameters. The power control module 240 controls a power inverter 244 that connects the battery system 104 to one or more loads 248 (e.g., vehicle loads). The battery management system 136 communicates with a propulsion controller 256, one or more other vehicle controllers 260, and / or a telematics controller 264 via a vehicle data bus 252. The components and functions of the battery management system 136 as described above are presented by way of example only, and other examples of the battery management system can include or omit various modules and associated functions.

[0077] Referring now to Figure 3 An example of the battery state estimation module 224 is shown in more detail. The battery state estimation module 224 includes a transient dynamics module 300, a transient state of power (SOP) module 304, and a steady state SOC module 308. The transient SOP module 304 and the steady state SOC module 308 receive a full battery state calculated by the transient dynamics module 300 (partly using a predicted voltage calculation) and calculate a transient SOP and a steady state SOC, respectively, based on the battery state.

[0078] For example, the transient dynamics module 300 implements a transient dynamics model (e.g., a model of transient dynamics) and a Kalman filter that updates the transient dynamics model based on actual battery behavior and accordingly calculates and outputs a battery state. For example, the transient dynamics module 300 receives battery measurements such as current, voltage, and temperature, updates its estimate of the battery state using these measurements and its previous estimate of the battery state, and predicts a battery voltage using the transient dynamics model. In one example, the difference between the predicted voltage and the measured voltage is used as a feedback signal to correct the battery state estimate. The correction is calculated as a product of a Kalman gain matrix and the feedback signal. The Kalman gain matrix can be computed by any of several methods known to those skilled in the art, such as an extended Kalman filter, a sigma point Kalman filter, or other related variants.

[0079] According to the principles of the present disclosure, the transient dynamics module 300 is further configured to calculate a battery state of the battery system 104 using an overpotential based on an equivalent constant current. For example, the transient dynamics model of the transient dynamics module 300 calculates a SOC, an equivalent constant current, an overpotential, and a predicted voltage based on estimated or measured values 312 including, but not limited to, a current, a temperature, and / or a voltage of the battery cell 200.

[0080] Referring now to Figure 4An example of the transient dynamics module 300 is described in more detail. The transient dynamics module 300 receives the measured battery cell temperature T and current I, and computes the corresponding state of charge SOC (e.g., based on coulomb counting, where x = SOC), open circuit voltage V OC , hysteresis voltage V hys , and overpotential V over , based on the temperature and current. For example, the transient dynamics module 300 includes an overpotential computation module 400 configured to compute the overpotential in accordance with the principles of the present disclosure. The transient dynamics module 300 computes the predicted voltage based on the open circuit voltage, hysteresis voltage, and overpotential (or based on the sum of the open circuit voltage, hysteresis voltage, and overpotential).

[0081] For example, the measured current is provided to a SOC computation module (e.g., a coulomb counter 404) configured to measure the amount of current consumption to compute the SOC of the battery cell. The current I provided to the coulomb counter 404 is divided by the capacity Q (i.e., multiplied by 1 / Q, as shown at 406) to obtain the rate of change of SOC, which is commonly referred to as the C-rate, and has units of reciprocal time. The coulomb counter 404 integrates this rate of change to obtain the current SOC, denoted as x in Figure 4 . The open circuit voltage is computed as a function of SOC (e.g., using an open circuit voltage calculator 408, where V OC = OCV(x)), and provided to an adder 410.

[0082] The current is also provided to a hysteresis module 412 that computes a hysteresis state corresponding to the hysteresis between the charge voltage and the discharge voltage, where the state is +1 for stable charging, -1 for stable discharging, and has intermediate values when the current direction changes. The hysteresis state is multiplied (e.g., using a multiplier 414) by the output of a voltage gap calculator 416 configured to compute the voltage gap V gap as a function of temperature and SOC.

[0083] The voltage gap corresponds to a hysteresis half-gap. The voltage required to charge the battery is greater than the voltage recovered from the battery during discharge. The hysteresis gap is the difference between the voltage required to charge the battery (charge voltage) and the voltage recovered from the battery during discharge (discharge voltage), which can vary as a function of state of charge, temperature, battery type and material, etc. Typically, if the battery is left idle in an open circuit state for an extended period, the battery voltage stabilizes near a midpoint between the charge voltage and the discharge voltage, which corresponds to the open circuit voltage. The voltage gap can be calculated as a function of the open circuit voltage, the charge voltage or the discharge voltage, and the voltage overpotential. The product of the hysteresis state and the voltage gap is provided to the adder 410.

[0084] The overpotential calculation module 400 is configured to calculate the equivalent constant current u cc and to calculate the overpotential. For example, the overpotential model 420 models the overpotential as a function of the equivalent constant current, the SOC, and the temperature, which can be implemented as a multi-dimensional lookup table, a mathematical model of the battery cell, etc. u cc , x , T The overpotential model 420 models the overpotential as a function of the equivalent constant current, the SOC, and the temperature, which can be implemented as a multi-dimensional lookup table, a mathematical model of the battery cell, etc.

[0085] For example, the weighting module 424 receives the measured current and one or more lag currents. Each of the lag currents corresponds to the measured current modified according to a respective lag current module 428. For example, the lag current modules 428 are implemented as low pass filters with different (e.g., progressively longer) time constants. The lag current modules 428 each output a lag current according to a respective time constant described in U.S. Patent No. 10,928,457. The number or quantity of lag current modules 428 and the size of the time constants can vary according to observed and / or modeled characteristics of the respective battery cell. Only three of the lag current modules 428 are shown by way of example. Although shown as being provided directly to the weighting module 424, in some examples, the measured current can be provided to the weighting module 424 through a high pass filter.

[0086] The weighting module 424 applies weighting factors 432 to the currents and lag currents (e.g., multiplies the currents and lag currents by respective weighting factors 432) and outputs weighted currents and lag currents. The weighted currents and lag currents are summed (e.g., at an adder 436) to produce a weighted sum, which corresponds to the equivalent constant current u cc .

[0087] The weighting factors 432 correspond to a function of r i (x, T), where r is a calibrated weight. More specifically, r0(x, T) through r3(x, T) are chosen such that In this way, the computed equivalent constant current is an approximation of the measured current that is relatively constant over a predetermined time period, and the overpotential module 420 computes the overpotential from the equivalent constant current, which is a weighted sum of the measured current and multiple hysteresis currents with progressively longer time constants. Summing the overpotential with the open-circuit voltage and the hysteresis voltage yields the predicted voltage.

[0088] Although the terms used in the foregoing are current, hysteresis current, and equivalent constant current. Figure 4 The signal input to the overpotential computation module 400 is shown as C-rate (I / Q). In this example, the terms C-rate, hysteresis C-rate, and equivalent constant C-rate replace current, hysteresis current, and equivalent constant current. The principles of operation in this example are similar to the principles of the computation using current, hysteresis current, and equivalent constant current, as long as the overpotential function A scaling factor is taken into account. For scale-independence and a more natural adaptation to battery degradation, a formulation in terms of C-rate is preferred, as the capacity Q decreases with battery age and usage.

[0089] Reference is now made to Figure 5 FIG. 5 shows an example method 500 for computing an overpotential of a battery cell in accordance with the present disclosure (e.g., implemented by the battery management system 136, the battery estimation module 224, the transient dynamics module 300, etc.). At 504, the method 500 measures one or more battery operating characteristics indicative of SOC, hysteresis, and overpotential, such as measured current and temperature. At 508, the method 500 computes a hysteresis current based on the measured current.

[0090] At 512, the method 500 computes an equivalent constant current corresponding to the measured current. For example, the equivalent constant current is a weighted sum of the measured current and the hysteresis current. In one example, the method 500 computes the weighted sum based on multiplying each of the measured current and the hysteresis current by a respective weighting factor, and the sum of the weighting factors is 1.

[0091] At 516, the method 500 computes an overpotential based on the equivalent constant current. For example, the method 500 computes the overpotential according to η( u cc , x , T ) At 520, the method 500 computes a predicted voltage of the battery cell based on the overpotential, the hysteresis voltage, and the SOC (e.g., an open-circuit voltage computed as a function of the SOC).

[0092] The foregoing description is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses. The broad teachings of the disclosure can be implemented in a variety of forms. Therefore, while this disclosure includes particular examples, the true scope of the disclosure should not be so limited since other modifications will become apparent upon a study of the drawings, specification, and claims. It should be understood that one or more steps within a method can be executed in different order (or concurrently) without altering the principles of the disclosure. Also, although each of the embodiments described herein is described as having certain features, any one or more of those described features can be implemented in any of the described embodiments and / or in combination with features described in any of the other embodiments without departing from the scope of the disclosure. In other words, the described embodiments are not mutually exclusive, and permutations of one or more embodiments' features are permitted without departing from the scope of the disclosure.

[0093] Spatial and functional relationships between elements (for example, between modules, circuit elements, semiconductor layers, etc.) are described using various terms, including "connected," "engaged," "coupled," "adjacent," "next to," "on top of," "above," "below," and "disposed on." Unless specifically described as "direct," relationships between components, as described above, can be indirect - that is, there are one or more intermediate components - spatially or functionally - that mediate the relationships between components. As used herein, the phrase "at least one of A, B, and C" should be construed to mean a logical (A OR B OR C) using the non-exclusive logical OR, and it should not be construed to mean "at least one of A, at least one of B, and at least one of C."

[0094] In the drawings, arrowhead pointed arrows generally illustrate the flow of information (such as data or instructions) that is of interest. For example, when element A exchanges information with element B, but the information that passes from element A to element B is relevant to the illustration, a one-way arrow can be directed from element A to element B. This one-way arrow does not imply that no other information is exchanged from element B to element A. Further, for information sent from element A to element B, element B can send requests for, or receive acknowledgements of, the information from element A.

[0095] In this application, including the following claims, the term "module" or the term "controller" can be replaced by the term "circuit." The term "module" can refer to, be part of, or include: an Application Specific Integrated Circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combination of

[0096] A module can include one or more interface circuits. In some examples, the interface circuits can include wired or wireless interfaces that are connected to a local area network (LAN), the Internet, a wide area network (WAN), or combinations thereof. The functionality of any given module of the present disclosure can be distributed among multiple modules that are connected via interface circuits. For example, multiple module can allow load balancing. In another example, a server (also known as remote, or cloud) module can accomplish some functionality on behalf of a client module.

[0097] As used in the detailed description, the terms "code" can include software, firmware, and / or microcode, and can refer to program, routines, functions, classes, data structures, and / or objects. The term "shared processor circuitry" encompasses a single processor circuitry executing some or all of the code from multiple modules. The term "group processor circuitry" encompasses a processor circuitry combined with additional processor circuitry to execute some or all of the code from one or more modules. References to multiple processor circuitries encompass a plurality of processor circuitries on discrete dies, a plurality of processor circuitries on a single die, multiple cores of a single processor circuitry, multiple threads of a single processor circuitry, or a combination of the above. The term "shared memory circuitry" encompasses a single memory circuitry storing some or all of the code from multiple modules. The term "group memory circuitry" encompasses a memory circuitry combined with additional memory to store some or all of the code from one or more modules.

[0098] The term "memory circuitry" is a subset of the term computer-readable medium. As used herein, the term "computer-readable medium" does not encompass transitory electromagnetic signals propagating through or carried by a medium (such as a carrier wave); therefore, the term computer-readable medium can be considered tangible and non-transitory. Non-limiting examples of a non-transitory, tangible computer-readable medium are nonvolatile memory circuits (such as flash memory circuits, erasable programmable read only memory (EPROM) circuits, or electrically erasable programmable read only memory (EEPROM) circuits), volatile memory circuits (such as static random access memory (SRAM) circuits or dynamic random access memory (DRAM) circuits), magnetic storage media (such as analog or digital magnetic tapes or magnetic hard drives), and optical storage media (such as optical discs like CDs, DVDs, or Blu-ray discs).

[0099] The apparatus and methods described in this application can be implemented in part or in whole through special purpose computer(s) configured to perform one or more specific functions, or by one or more general purpose computer(s) configured to perform the specific functions described in this application by virtue of having software implementing one or more specific functional aspects of the application embodied in the computer program. The basic input / output system (BIOS), device drivers, operating system, and application program interfaces (APIs) associated with the various techniques described herein are stored in the system memory and / or the persistent storage. The software is loaded from the persistent storage into the system memory and executed by the CPU(s) as described above.

[0100] The computer program can include or rely on the storage of data in a non-transitory, tangible, computer-readable storage medium. The computer program can be embodied in a computer program product. The computer program can be distributed over network coupled computer systems so that the computer program segments can be stored and executed in a distributed fashion.

[0101] The computer program can include: (i) descriptive text to be parsed, such as HTML (HyperText Markup Language), XML (Extensible Markup Language), or JSON (JS Object Notation), (ii) assembly code, (iii) object code generated from source code using an assembler, (iv) object code generated from source code using a compiler, (v) source code for execution by an interpreter, (vi) source code for compilation and execution by a just-in-time compiler, etc. As examples only, source code can be written using syntaxes including: C, C++, C#, Objective-C, Swift, Haskell, Go, SQL, R, Lisp, Java®, Fortran, Perl, Pascal, Curl, OCaml, Javascript®, HTML5 (HyperText Markup Language Version 5), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Flash®, Visual Basic®, Lua, MATLAB, SIMULINK, and Python®.

Claims

1. A system comprising: a state of charge (SOC) computation module configured to compute an SOC of a battery cell based on a measured current of the battery cell; and an overpotential computation module configured to receive the measured current and output a lag current based on the measured current and a corresponding time constant, output a weighted measured current and a weighted lag current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is 1, compute an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted lag current, and compute an overpotential of the battery cell based on the equivalent constant current, wherein the system is configured to output a predicted voltage of the battery cell based on the computed SOC and the computed overpotential of the battery cell.

2. The system of claim 1, wherein the overpotential computation module comprises a plurality of lag current modules configured to compute the lag current.

3. The system of claim 2, wherein the lag current module corresponds to a low pass filter.

4. The system of claim 1, wherein the weighting factors are a function of the SOC and temperature of the battery cell.

5. The system of claim 1, wherein the equivalent constant current is a sum of the weighted current and the weighted lag current.

6. The system of claim 1, wherein, the overpotential computation module is configured to compute the overpotential further based on the SOC and temperature of the battery cell.

7. The system of claim 6, wherein the overpotential computation module is configured to compute the overpotential using a lookup table.

8. The system of claim 1, wherein the predicted voltage is a sum of an open circuit voltage and the overpotential.

9. The system of claim 1, wherein the predicted voltage is a sum of an open circuit voltage, an overpotential, and a hysteresis voltage of the battery cell.

10. The system of claim 9, further comprising a hysteresis module configured to compute the hysteresis voltage of the battery cell.

11. A method comprising: computing an SOC of a battery cell based on a measured current of the battery cell; receiving the measured current and outputting a lag current based on the measured current and a corresponding time constant; outputting a weighted measured current and a weighted lag current based on a plurality of weighting factors, wherein a sum of the plurality of weighting factors is 1; computing an equivalent constant current corresponding to the measured current based on the weighted measured current and the weighted lag current; computing an overpotential of the battery cell based on the equivalent constant current; and outputting a predicted voltage of the battery cell based on the computed SOC and the computed overpotential of the battery cell.

12. The method of claim 11, further comprising outputting the lag current using a low pass filter.

13. The method of claim 11, wherein the weighting factors are a function of the SOC and temperature of the battery cell.

14. The method of claim 11, further comprising summing the weighted current and the weighted hysteresis current to calculate the equivalent constant current.

15. The method of claim 11, further comprising calculating the overpotential further based on the SOC and temperature of the battery cell.

16. The method of claim 15, further comprising calculating the overpotential using a lookup table.

17. The method of claim 16, wherein the predicted voltage is a sum of an open circuit voltage and the overpotential.

18. The method of claim 11, wherein the predicted voltage is a sum of an open circuit voltage, the overpotential, and a hysteresis voltage of the battery cell.

Images