Battery charge state determination method and device, equipment, storage medium and vehicle

Abstract

The invention relates to a battery charge state determination method and device, equipment, a storage medium and a vehicle. The method comprises the following steps: acquiring a state equation and an output equation of an equivalent circuit model according to model parameters of the equivalent circuit model of the battery; according to the state equation and the output equation, in a continuous sampling time window, adopting a global optimal algorithm to fit target state parameters of the battery so as to obtain an initial state of charge of the battery; and correcting the current state of charge of the battery according to the initial state of charge. According to the global optimal battery SOC determination algorithm provided by the embodiment of the invention, the battery SOC can be estimated in real time by using the global optimal algorithm by using the battery voltage, current and temperature sampling data in a short continuous sampling time window in the uninterrupted charging and discharging process of the battery. The algorithm has the advantages of being good in robustness, high in estimation precision and easy to implement.

Description

Technical Field

[0001] The present disclosure relates to the field of battery technology, and in particular to a method, device, equipment, storage medium and vehicle for determining a battery state of charge. Background Art

[0002] The battery's SOC (State of Charge) is the ratio of the remaining dischargeable capacity of the battery to the dischargeable capacity when the battery is fully charged, which represents the remaining dischargeable capacity of the battery. During the use of the battery, the real-time and accurate estimation of SOC is one of the important tasks of the battery management system (BMS), and is also an important basis for the entire vehicle's charge and discharge control strategies. However, due to the complexity of the battery's own structure and electrochemical characteristics, the battery SOC cannot be obtained through direct measurement, but can only be obtained through external measurements of the battery, including current, terminal voltage, temperature, etc., and the use of relevant characteristic curves and calculation methods to complete the indirect estimation of SOC.

[0003] Currently, common methods for estimating battery SOC include the ampere-hour integration method, the open circuit voltage method, and the online estimation algorithm based on the battery model and state observer.

[0004] However, the ampere-hour integration method has the problem of error accumulation and cannot guarantee the accuracy of SOC estimation when the battery is working for a long time. The open circuit voltage method has the problem of requiring the battery to be stationary for a period of time and cannot obtain the battery SOC in real time online. The online estimation algorithm of the battery model and state observer has the disadvantages of poor robustness and complex algorithm parameter adjustment, which limits its practical application in engineering. Summary of the invention

[0005] In order to overcome the problems existing in the related art, the present disclosure provides a battery state of charge determination method, device, equipment, storage medium and vehicle. A globally optimal battery SOC estimation algorithm is proposed, which can use the battery voltage, current and temperature sampling data in a short time window in the past during the uninterrupted charging and discharging process of the battery to estimate the battery SOC in real time using the global optimal algorithm. The algorithm has the characteristics of good robustness, high estimation accuracy and simple implementation.

[0006] According to a first aspect of an embodiment of the present disclosure, a method for determining a battery state of charge is provided, the method comprising:

[0007] According to the model parameters of the equivalent circuit model of the battery, a state equation and an output equation of the equivalent circuit model are obtained;

[0008] According to the state equation and the output equation, within a continuous sampling time window, a global optimal algorithm is used to fit the target state parameters of the battery to obtain an initial state of charge of the battery;

[0009] The current state of charge of the battery is corrected according to the initial state of charge.

[0010] Optionally, the equivalent circuit model of the battery includes: an open circuit voltage source, an ohmic internal resistance, a polarization internal resistance and a polarization capacitor;

[0011] The polarization internal resistance and the polarization capacitor are connected in parallel, and a parallel circuit formed by the polarization internal resistance and the polarization capacitor is connected in parallel with the ohmic internal resistance and the open circuit voltage source in series;

[0012] The voltage of the open circuit voltage source and the state of charge of the battery have a single mapping relationship.

[0013] Optionally, the state equation is a description equation of the target state parameter, and the target state parameter includes a vector consisting of a sampling point state of charge and a sampling point polarization current of the battery.

[0014] Optionally, the output equation is a description equation of the output voltage of the equivalent circuit model.

[0015] Optionally, fitting the target state parameters of the battery using a global optimal algorithm within a continuous sampling time window according to the state equation and the output equation to obtain the initial state of charge of the battery includes:

[0016] In the continuous sampling time window, sampling the current and voltage of the battery to obtain a sampling current sequence and a sampling voltage sequence of the battery;

[0017] According to the sampling current sequence and the output equation, an output voltage sequence of the equivalent circuit model is obtained;

[0018] According to the sampled voltage sequence and the output voltage sequence, a global optimal algorithm is used to fit the initial state of charge of the equivalent circuit model.

[0019] Optionally, fitting the initial state of charge of the equivalent circuit model using a global optimal algorithm according to the sampled voltage sequence and the output voltage sequence includes:

[0020] Obtaining a sum of squares of errors between the sampled voltage sequence and the output voltage sequence;

[0021] Obtaining the target state parameter that minimizes the sum of squared errors;

[0022] According to the target state parameter, an initial state of charge of the equivalent circuit model is obtained.

[0023] Optionally, the step of fitting the target state parameters of the battery using a global optimal algorithm to obtain the initial state of charge of the battery is performed by a central domain controller of the vehicle.

[0024] According to a second aspect of an embodiment of the present disclosure, there is provided a battery state of charge determination device, comprising:

[0025] A first acquisition module, used for acquiring a state equation and an output equation of the equivalent circuit model of the battery according to a model parameter of the equivalent circuit model of the battery;

[0026] A second acquisition module is used to fit the target state parameters of the battery using a global optimal algorithm within a continuous sampling time window according to the state equation and the output equation to obtain an initial state of charge of the battery;

[0027] The correction module is used to correct the current state of charge of the battery according to the initial state of charge.

[0028] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0029] processor;

[0030] a memory for storing processor-executable instructions;

[0031] The processor is configured to: execute the executable instructions to implement any one of the methods in the first aspect.

[0032] According to a fourth aspect of an embodiment of the present disclosure, there is provided a computer-readable storage medium on which computer program instructions are stored, and when the program instructions are executed by a processor, the steps of any one of the methods described in the first aspect are implemented.

[0033] According to a fifth aspect of an embodiment of the present disclosure, a chip is provided, comprising a processor and an interface; the processor is used to read instructions to execute any one of the methods described in the first aspect.

[0034] According to a sixth aspect of an embodiment of the present disclosure, a vehicle is provided, comprising the electronic device described in the third aspect.

[0035] In summary, the disclosed embodiment provides a method for determining the state of charge of a battery, the method comprising: obtaining the state equation and the output equation of the equivalent circuit model according to the model parameters of the equivalent circuit model of the battery; fitting the target state parameters of the battery according to the state equation and the output equation within a continuous sampling time window using a global optimal algorithm to obtain the initial state of charge of the battery; and correcting the current state of charge of the battery according to the initial state of charge. The disclosed embodiment proposes a globally optimal battery SOC determination algorithm, which can use the battery voltage, current and temperature sampling data within a shorter continuous sampling time window during the uninterrupted charging and discharging process of the battery to estimate the battery SOC in real time using a global optimal algorithm. The algorithm has the characteristics of good robustness, high estimation accuracy and simple implementation.

[0036] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0038] Figure 1 is a schematic diagram of a first-order RC equivalent circuit model of a battery according to an exemplary embodiment.

[0039] Figure 2 The figure is a schematic diagram of a SOC estimation algorithm framework based on a state observer according to an exemplary embodiment.

[0040] Figure 3 The figure is a schematic diagram of a SOC estimation algorithm framework based on global optimization according to an exemplary embodiment.

[0041] Figure 4 The figure is a flow chart of a method for determining a battery state of charge according to an exemplary embodiment.

[0042] Figure 5 The figure is a flow chart of a method for determining a battery state of charge according to an exemplary embodiment.

[0043] Figure 6 The figure is a flow chart of a method for determining a battery state of charge according to an exemplary embodiment.

[0044] Figure 7 The figure is a schematic diagram showing a battery discharge data segment according to an exemplary embodiment.

[0045] Figure 8The figure is a schematic diagram showing a global optimal algorithm for fitting battery voltage and SOC estimation results according to an exemplary embodiment.

[0046] Fig. 9 It is a schematic diagram of a SOC algorithm architecture based on a BMS and a central domain controller according to an exemplary embodiment.

[0047] Fig.10 The figure is a block diagram of a device for determining a battery state of charge according to an exemplary embodiment.

[0048] Fig.11 It is a block diagram of an electronic device according to an exemplary embodiment.

[0049] Fig.12 It is a block diagram of an electronic device according to an exemplary embodiment.

[0050] Fig.13 is a block diagram of a vehicle according to an exemplary embodiment. DETAILED DESCRIPTION

[0051] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0052] It should be understood that the term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0053] It should be noted that the concepts of "first", "second", etc. mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units. The modifications of "one" and "multiple" mentioned in the present disclosure are illustrative and not restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more". In the description of the present disclosure, unless otherwise specified, "multiple" refers to two or more than two, and other quantifiers are similar; "at least one item", "one item or multiple items" or similar expressions refer to any combination of these items, including any combination of single items or plural items.

[0054] Although operations or steps are described in a specific order in the drawings in the embodiments of the present disclosure, it should not be understood that it is required to perform these operations or steps in the specific order shown or in a serial order, or to perform all the operations or steps shown to obtain the desired results. In the embodiments of the present disclosure, these operations or steps can be performed in series; these operations or steps can also be performed in parallel; or some of these operations or steps can be performed.

[0055] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information. It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user in an appropriate manner in accordance with relevant laws and regulations and the user's authorization should be obtained. The present disclosure is described below in conjunction with specific embodiments.

[0056] First, the application scenario of the present disclosure is described. Currently, common methods for estimating battery SOC include the ampere-hour integration method, the open circuit voltage method, and an online estimation algorithm based on a battery model and a state observer.

[0057] The ampere-hour integration method is affected by current measurement errors, battery capacity errors, and initial battery SOC errors, and the errors will continue to accumulate over time, and the SOC estimation accuracy of the battery cannot be guaranteed for long-term operation.

[0058] Open Circuit Voltage (OCV) is the terminal voltage of the battery after it has been fully rested, that is, the electromotive force between the positive and negative electrodes of the battery. OCV can be used to more accurately correct the SOC. In the prior art, the general premise for obtaining OCV is that the battery has been rested for a long enough time. Some papers and patents also mention the use of battery terminal voltage sampling after resting for several minutes to predict and estimate OCV. But in short, the open circuit voltage method cannot obtain OCV during the uninterrupted charging and discharging process of the battery.

[0059] In order to solve the problem of error accumulation in calculating battery SOC by the ampere-hour integration method, and the problem that the open circuit voltage method cannot calculate the corrected SOC during the uninterrupted charging and discharging process of the battery, an online SOC estimation algorithm based on a battery model and a state observer is usually used. The online SOC estimation algorithm based on a battery model and a state observer first establishes a mathematical model for the battery. The common battery model is the equivalent circuit model (ECM). Secondly, based on the established battery model, the state estimator algorithm is applied to perform real-time recursive iterative estimation of the battery state including SOC. The specific state estimator algorithm includes but is not limited to recursive least squares method, Kalman filter and its extended form, particle filter and its extended form, etc. However, this method has the disadvantages of poor robustness and complex algorithm parameter adjustment, which limits its practical application in engineering.

[0060] Figure 1 FIG. 1 is a schematic diagram showing a first-order RC equivalent circuit model of a battery according to an exemplary embodiment. Figure 1 As shown, the circuit is a battery equivalent circuit model including an ohmic internal resistance and a first-order RC unit, and the parameters included are: ohmic internal resistance R0, polarization internal resistance R1 and polarization capacitance C1. These equivalent circuit model parameters are generally obtained through standard operating condition testing and offline parameter identification methods, and of course, they can also be identified online during the actual use of the battery. It should be noted that in actual engineering applications, the number of parallel RCs in the equivalent circuit model can be selected according to the specific application, such as a second-order or third-order RC model.

[0061] Figure 2 FIG. 1 is a schematic diagram of a SOC estimation algorithm framework based on a state observer according to an exemplary embodiment. Figure 2 As shown in the figure, the state observer (or state estimator) can estimate the internal state of the controlled system based on the input and output of the controlled system under the premise of knowing the framework of the controlled system. In the specific battery SOC estimation problem, the controlled system is the battery system, and the battery system can be described using the equivalent circuit model introduced above; and the commonly used state observers include: recursive least squares method, Kalman filter, particle filter, etc.

[0062] However, no matter which state observer is used, it usually faces the following difficulties in practical applications:

[0063] First, due to the time-varying nonlinear characteristics of the battery system, it is difficult for the state observer to simultaneously meet the SOC estimation accuracy under different temperatures, SOC ranges, and current rates. In other words, it is difficult to ensure that the state observer has sufficient robustness while having sufficient estimation accuracy and convergence speed.

[0064] Secondly, in order to obtain appropriate state observer parameters, a large amount of battery testing and algorithm simulation work is often required. Taking the Extended Kalman Filter (EKF), a state observer commonly used in engineering applications, as an example, in the SOC estimation practice applied to the first-order RC equivalent circuit model of the battery, the parameters that need to be adjusted include 2 initial state values, 2 initial covariance matrix values, 2 process noise parameters, and 1 output noise parameter, a total of 7 parameters. In addition, in order to adapt to the estimation accuracy under different temperatures, SOC ranges and current rates, multiple parameters of these 7 parameters may need to be calibrated separately. For example, the process noise parameters and output noise parameters generally need to be calibrated as two-dimensional lookup tables based on SOC and temperature. Such complicated calibration and parameter adjustment work limits its practical application in engineering.

[0065] Figure 3 is a schematic diagram of a SOC estimation algorithm framework based on global optimization according to an exemplary embodiment. In view of the shortcomings of the existing SOC calculation method, the present disclosure proposes a battery SOC estimation algorithm framework based on global optimization. Figure 3 As shown, this algorithm caches a time window in the past (continuous sampling time window). For example, 300s of continuous battery voltage, current and temperature sampling data are taken here, combined with the battery model, and the optimal battery SOC estimation is fitted based on the global optimal algorithm. According to the current and temperature of the real battery, the sampled voltage of the battery is obtained in the continuous sampling time window, and the error value between the sampled voltage and the output voltage of the state space equation of the battery model is sent to the global optimal algorithm module. The output of this module is sent to the battery model. At the same time, the current and temperature of the real battery in the continuous sampling time window are also sent to the battery model. After iterative calculations are performed on the state space equation, the output voltage of the state space equation is output. The global optimal algorithm module inputs the initial SOC value for iterative calculations, and the optimal battery SOC estimation can be fitted based on the global optimal algorithm.

[0066] Figure 4 FIG. 1 is a flow chart of a method for determining a battery state of charge according to an exemplary embodiment. Figure 4 As shown, the embodiment of the present disclosure provides a method for determining a battery state of charge, which may include the following steps:

[0067] In step S10, the state equation and output equation of the equivalent circuit model are obtained according to the model parameters of the equivalent circuit model of the battery.

[0068] In this step, the state equation and output equation of the equivalent circuit model are obtained according to the model parameters of the equivalent circuit model of the battery. Exemplarily, the model parameters of the equivalent circuit model of the battery may include an open circuit voltage source, an ohmic internal resistance, a polarization internal resistance, and a polarization capacitance. The state equation of the battery is a description equation of the target state parameters, and the target state parameters include a vector consisting of the state of charge at the sampling point of the battery and the polarization current at the sampling point. The output equation is a description equation of the output voltage of the battery equivalent circuit model.

[0069] In step S20, according to the state equation and the output equation, a global optimal algorithm is used to fit the target state parameters of the battery within a continuous sampling time window to obtain the initial state of charge of the battery.

[0070] In this step, according to the state equation and the output equation, the target state parameters of the battery are fitted using a global optimal algorithm within a continuous sampling time window to obtain the initial state of charge of the battery. Exemplarily, the current and voltage of the battery can be sampled within a continuous sampling time window to obtain a sampled current sequence and a sampled voltage sequence of the battery. Then, based on the sampled current sequence and the output equation, the output voltage sequence of the battery equivalent circuit model is obtained. Then, based on the sampled voltage sequence and the output voltage sequence, the initial state of charge of the battery equivalent circuit model is fitted using a global optimal algorithm.

[0071] In step S30, the current state of charge of the battery is corrected according to the initial state of charge.

[0072] In this step, the current state of charge of the battery is corrected according to the initial state of charge. Exemplarily, the correction formula of the current state of charge SOC of the battery can be shown as follows:

[0073]

[0074]

[0075] Among them, C N is the rated full charge capacity of the battery, I is the absolute value of the battery current, η is the battery charge and discharge efficiency, and SOC0 is the initial state of charge of the battery.

[0076] Among them, formula 1 is applicable to the battery discharging situation, and formula 2 is applicable to the battery charging situation.

[0077] In summary, the disclosed embodiment provides a method for determining the state of charge of a battery, the method comprising: obtaining the state equation and the output equation of the equivalent circuit model according to the model parameters of the equivalent circuit model of the battery; fitting the target state parameters of the battery according to the state equation and the output equation within a continuous sampling time window using a global optimal algorithm to obtain the initial state of charge of the battery; and correcting the current state of charge of the battery according to the initial state of charge. The disclosed embodiment proposes a globally optimal battery SOC determination algorithm, which can use the battery voltage, current and temperature sampling data within a shorter continuous sampling time window during the uninterrupted charging and discharging process of the battery to estimate the battery SOC in real time using a global optimal algorithm. The algorithm has the characteristics of good robustness, high estimation accuracy and simple implementation.

[0078] In some embodiments, Figure 1 As shown, taking the first-order RC equivalent circuit model as an example, the equivalent circuit model of the battery includes: an open circuit voltage source OCV, an ohmic internal resistance R0, a polarization internal resistance R1 and a polarization capacitor C1. Among them, the polarization internal resistance R1 and the polarization capacitor C1 are connected in parallel, and the parallel circuit composed of the polarization internal resistance R1 and the polarization capacitor C1 is connected in series with the ohmic internal resistance R0 and the open circuit voltage source OCV. The voltage of the open circuit voltage source OCV has a single mapping relationship with the state of charge of the battery, that is, different voltages of the open circuit voltage source OCV correspond to different states of charge of the battery, and there is no situation where different voltages of the open circuit voltage source OCV correspond to the same state of charge of the battery.

[0079] In some embodiments, the state equation is a description equation of the target state parameter, and the target state parameter includes a vector consisting of the state of charge at the sampling point of the battery and the polarization current at the sampling point. Exemplarily, the state equation can be shown as the following formula:

[0080]

[0081] Among them, R0, R1, C1 are the ohmic internal resistance, polarization internal resistance and polarization capacitance in the first-order equivalent circuit model, Q is the battery capacity, OCV(soc) is the SOC-OCV lookup table (this table is related to temperature, and the corresponding data of SOC-OCV is different at different temperatures), Δt is the sampling period, i k is the sampling current at time k, soc k and i R1,k is the current of the SOC and R1C1 parallel circuit at time k.

[0082] In some embodiments, the output equation is a description equation of the output voltage of the equivalent circuit model. Exemplarily, the output equation can be shown as the following formula:

[0083] f k =OCV(SOC k )+R1 i R1,k +R0i k Formula 4

[0084] Among them, R0 and R1 are the ohmic internal resistance in the first-order equivalent circuit model, the polarization internal resistance OCV(soc) is the SOC-OCV lookup table (this table is related to temperature, and the corresponding data of SOC-OCV at different temperatures are different), i k is the sampling current at time k, soc k and i R1,k is the current of the SOC and R1C1 parallel circuit at time k, f k is the model output voltage at time k.

[0085] Figure 5 FIG. 1 is a flow chart of a method for determining a battery state of charge according to an exemplary embodiment. Figure 5 As shown, according to the state equation and the output equation, within a continuous sampling time window, a global optimal algorithm is used to fit the target state parameters of the battery to obtain the initial state of charge of the battery, which may include the following steps:

[0086] In step S201, the current and voltage of the battery are sampled within the continuous sampling time window to obtain a sampled current sequence and a sampled voltage sequence of the battery.

[0087] In this step, the current and voltage of the battery are sampled within a continuous sampling time window, such as 300 seconds. For example, the data is sampled once per second. Then, 300 data sequences of the current and voltage of the battery can be obtained within 300 seconds, that is, the sampling current sequence i of the battery. k and the sampling voltage sequence v k .

[0088] In step S202, an output voltage sequence of the equivalent circuit model is obtained according to the sampled current sequence and the output equation.

[0089] In this step, according to the sampling current sequence i k And the output equation (Formula 4) to obtain the output voltage sequence f(i k ,β). Among them, β=[soc0,i R1,0 ] is the target state parameter of the fitting.

[0090] In step S203, a global optimal algorithm is used to fit the initial state of charge of the equivalent circuit model according to the sampled voltage sequence and the output voltage sequence.

[0091] In this step, according to the sampling voltage sequence v k And the output voltage sequence f(i k ,β), and the global optimal algorithm is used to fit the initial state of charge soc0 of the equivalent circuit model.

[0092] Figure 6 FIG. 1 is a flow chart of a method for determining a battery state of charge according to an exemplary embodiment. Figure 6 As shown, the step of fitting the initial state of charge of the equivalent circuit model using a global optimal algorithm according to the sampled voltage sequence and the output voltage sequence may include the following steps:

[0093] In step S2031, the sum of square errors between the sampled voltage sequence and the output voltage sequence is obtained.

[0094] In this step, the sampled voltage sequence v is obtained. k And the output voltage sequence f(i k ,β) Where m is the number of continuous sampling points.

[0095] In step S2032, the target state parameter that minimizes the sum of squared errors is obtained.

[0096] In this step, the target state parameters that minimize the sum of squared errors are obtained. Exemplary, minimum target state parameters It can be obtained by the following formula:

[0097]

[0098] Among them, i k is the sampling current, v k is the sampling voltage, β=[soc0,i R1,0 ] is the fitting target state parameter, and m is the number of continuous sampling points. The solution belongs to the category of nonlinear least squares and requires iterative solution. The specific solution algorithms that can be used include but are not limited to the Gauss-Newton algorithm, the Levenberg-Marquardt algorithm, etc.

[0099] In step S2033, the initial state of charge of the equivalent circuit model is acquired according to the target state parameter.

[0100] In this step, according to the target state parameter Get the initial state of charge soc0 of the equivalent circuit model. Directly read the target state parameters Soc0 in the vector will do.

[0101] Based on the fitted initial state of charge soc0, the SOC of the battery at the current moment can be corrected. The specific method is shown in the above formula 1-2.

[0102] Figure 7 FIG. 1 is a schematic diagram showing a battery discharge data segment according to an exemplary embodiment. Figure 7 As shown, the current, voltage and temperature sampling curves of the ternary lithium-ion battery used by the inventor in a certain application during the discharge process in a 300s time window, wherein the battery temperatures of the two segments of data are 25 degrees Celsius and 0 degrees Celsius, respectively.

[0103] Figure 8 FIG. 1 is a schematic diagram showing a global optimal algorithm for fitting battery voltage and SOC estimation results according to an exemplary embodiment. Figure 8 As shown, a sampling period of 1s is used in combination with a first-order RC equivalent circuit model to perform a global optimal estimation of the battery SOC. The figure shows a comparison between the output voltage and battery SOC fitted by the algorithm and the actual sampling voltage and true SOC.

[0104] It can be seen that the voltage fit of the two sets of data at 25 degrees Celsius and 0 degrees Celsius is very good, and the SOC estimation errors are 0.7% and 1.5% respectively. It is possible to achieve an SOC estimation accuracy of less than 2% under different battery temperature conditions by using only 300s of sampling data without relying on the accuracy of the initial SOC value, thus proving the feasibility and effectiveness of the global optimal algorithm for battery SOC estimation proposed in the present disclosure.

[0105] In summary, the disclosed embodiment provides a method for determining the state of charge of a battery, the method comprising: obtaining the state equation and the output equation of the equivalent circuit model according to the model parameters of the equivalent circuit model of the battery; fitting the target state parameters of the battery according to the state equation and the output equation within a continuous sampling time window using a global optimal algorithm to obtain the initial state of charge of the battery; and correcting the current state of charge of the battery according to the initial state of charge. The disclosed embodiment proposes a globally optimal battery SOC determination algorithm, which can use the battery voltage, current and temperature sampling data within a shorter continuous sampling time window during the uninterrupted charging and discharging process of the battery to estimate the battery SOC in real time using a global optimal algorithm. The algorithm has the characteristics of good robustness, high estimation accuracy and simple implementation.

[0106] Fig. 9FIG. 1 is a schematic diagram showing a SOC algorithm architecture based on a BMS and a central domain controller according to an exemplary embodiment. Fig. 9 As shown, since the global optimal algorithm of the present disclosure requires a certain amount of computing power support, the step of fitting the target state parameters of the battery using the global optimal algorithm to obtain the initial state of charge of the battery can be executed by the central domain controller of the vehicle.

[0107] Fig.10 FIG. 1 is a block diagram of a device for determining a battery state of charge according to an exemplary embodiment. Fig.10 As shown, an embodiment of the present disclosure provides a device for determining a battery state of charge, and the device 1000 may include the following modules:

[0108] The first acquisition module 1001 is used to acquire the state equation and the output equation of the equivalent circuit model according to the model parameters of the equivalent circuit model of the battery.

[0109] The second acquisition module 1002 is used to fit the target state parameters of the battery using a global optimal algorithm within a continuous sampling time window according to the state equation and the output equation to obtain the initial state of charge of the battery.

[0110] The correction module 1003 is used to correct the current state of charge of the battery according to the initial state of charge.

[0111] Optionally, the equivalent circuit model of the battery includes: an open circuit voltage source, an ohmic internal resistance, a polarization internal resistance and a polarization capacitor;

[0112] The polarization internal resistance and the polarization capacitor are connected in parallel, and a parallel circuit formed by the polarization internal resistance and the polarization capacitor is connected in parallel with the ohmic internal resistance and the open circuit voltage source in series;

[0113] The voltage of the open circuit voltage source and the state of charge of the battery have a single mapping relationship.

[0114] Optionally, the state equation is a description equation of the target state parameter, and the target state parameter includes a vector consisting of a sampling point state of charge and a sampling point polarization current of the battery.

[0115] Optionally, the output equation is a description equation of the output voltage of the equivalent circuit model.

[0116] Optionally, the second acquisition module 1002 includes an algorithm fitting submodule, which is configured to sample the current and voltage of the battery within the continuous sampling time window to obtain a sampled current sequence and a sampled voltage sequence of the battery;

[0117] According to the sampling current sequence and the output equation, an output voltage sequence of the equivalent circuit model is obtained;

[0118] According to the sampled voltage sequence and the output voltage sequence, a global optimal algorithm is used to fit the initial state of charge of the equivalent circuit model.

[0119] Optionally, the algorithm fitting submodule includes an initial state of charge acquisition submodule, which is configured to:

[0120] Obtaining a sum of squares of errors between the sampled voltage sequence and the output voltage sequence;

[0121] Obtaining the target state parameter that minimizes the sum of squared errors;

[0122] According to the target state parameter, an initial state of charge of the equivalent circuit model is obtained.

[0123] Optionally, the step of fitting the target state parameters of the battery using a global optimal algorithm to obtain the initial state of charge of the battery is performed by a central domain controller of the vehicle.

[0124] In summary, the disclosed embodiment provides a battery state of charge determination device, comprising: a first acquisition module, used to acquire the state equation and output equation of the equivalent circuit model according to the model parameters of the equivalent circuit model of the battery; a second acquisition module, used to fit the target state parameters of the battery according to the state equation and the output equation within a continuous sampling time window using a global optimal algorithm to acquire the initial state of charge of the battery; a correction module, used to correct the current state of charge of the battery according to the initial state of charge. The disclosed embodiment proposes a globally optimal battery SOC determination algorithm, which can use the battery voltage, current and temperature sampling data within a shorter continuous sampling time window during the uninterrupted charging and discharging process of the battery to estimate the battery SOC in real time using a global optimal algorithm. The algorithm has the characteristics of good robustness, high estimation accuracy and simple implementation.

[0125] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0126] The present disclosure also provides a computer-readable storage medium having computer program instructions stored thereon. When the program instructions are executed by a processor, the steps of the battery state of charge determination method provided by the present disclosure are implemented.

[0127] Fig.111 is a block diagram of an electronic device according to an exemplary embodiment. For example, the electronic device 1100 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0128] Reference Fig.11 , the electronic device 1100 may include one or more of the following components: a processing component 1102 , a memory 1104 , a power component 1106 , a multimedia component 1108 , an audio component 1110 , an input / output interface 1112 , a sensor component 1114 , and a communication component 1116 .

[0129] The processing component 1102 generally controls the overall operation of the electronic device 1100, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 1102 may include one or more processors 1120 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 1102 may include one or more modules to facilitate the interaction between the processing component 1102 and other components. For example, the processing component 1102 may include a multimedia module to facilitate the interaction between the multimedia component 1108 and the processing component 1102.

[0130] The memory 1104 is configured to store various types of data to support operations on the electronic device 1100. Examples of such data include instructions for any application or method operating on the electronic device 1100, contact data, phone book data, messages, pictures, videos, etc. The memory 1104 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0131] The power supply component 1106 provides power to various components of the electronic device 1100. The power supply component 1106 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 1100.

[0132] The multimedia component 1108 includes a screen that provides an output interface between the electronic device 1100 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1108 includes a front camera and / or a rear camera. When the electronic device 1100 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0133] The audio component 1110 is configured to output and / or input audio signals. For example, the audio component 1110 includes a microphone (MIC), and when the electronic device 1100 is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 1104 or sent via the communication component 1116. In some embodiments, the audio component 1110 also includes a speaker for outputting audio signals.

[0134] The input / output interface 1112 provides an interface between the processing component 1102 and the peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0135] The sensor assembly 1114 includes one or more sensors for providing various aspects of status assessment for the electronic device 1100. For example, the sensor assembly 1114 can detect the open / closed state of the electronic device 1100, the relative positioning of components, such as the display and keypad of the electronic device 1100, and the sensor assembly 1114 can also detect the position change of the electronic device 1100 or a component of the electronic device 1100, the presence or absence of user contact with the electronic device 1100, the orientation or acceleration / deceleration of the electronic device 1100, and the temperature change of the electronic device 1100. The sensor assembly 1114 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 1114 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 1114 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0136] The communication component 1116 is configured to facilitate wired or wireless communication between the electronic device 1100 and other devices. The electronic device 1100 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 1116 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1116 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0137] In an exemplary embodiment, the electronic device 1100 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0138] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1104 including instructions, and the instructions can be executed by a processor 1120 of the electronic device 1100 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0139] In addition to being an independent device, the above-mentioned electronic device can also be a part of an independent electronic device. For example, in one embodiment, the electronic device can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be an IC or a collection of multiple ICs; the chip can include but is not limited to the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), SOC (System on Chip, SoC), etc. The above-mentioned integrated circuit or chip can be used to execute executable instructions (or codes) to implement the above-mentioned battery charge state determination method. The executable instructions can be stored in the integrated circuit or chip, or can be obtained from other electronic devices or devices. For example, the integrated circuit or chip includes a processor, a memory, and an interface for communicating with other electronic devices. The executable instruction can be stored in the memory, and when the executable instruction is executed by the processor, the above-mentioned battery charge state determination method is implemented; alternatively, the integrated circuit or chip can receive the executable instruction through the interface and transmit it to the processor for execution, so as to implement the above-mentioned battery charge state determination method.

[0140] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable electronic device. The computer program has a code portion for executing the above-mentioned battery state of charge determination method when executed by the programmable electronic device.

[0141] Fig.12 1 is a block diagram of an electronic device according to an exemplary embodiment. For example, the electronic device 1200 may be provided as a server. Fig.12 The electronic device 1200 includes a processing component 1222, which further includes one or more processors, and a memory resource represented by a memory 1232 for storing instructions executable by the processing component 1222, such as an application. The application stored in the memory 1232 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1222 is configured to execute instructions to perform the above-mentioned battery charge state determination method.

[0142] The electronic device 1200 may further include a power supply component 1226 configured to perform power management of the electronic device 1200, a wired or wireless network interface 1250 configured to connect the electronic device 1200 to a network, and an input / output interface 1258. The electronic device 1200 may operate based on an operating system stored in the memory 1232.

[0143] Fig.13 FIG. 1 is a block diagram of a vehicle according to an exemplary embodiment. Fig.13 As shown, the embodiment of the present disclosure provides a vehicle 1300, including the electronic device 1100 provided in the above embodiment. Fig.13 , the vehicle 1300 may include various subsystems, such as an infotainment system 1310, a perception system 1320, a decision control system 1330, a drive system 1340, and a computing platform 1350. The vehicle 1300 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 1300 may be interconnected by wire or wireless means.

[0144] In some embodiments, the infotainment system 1310 may include a communication system, an entertainment system, and a navigation system, etc.

[0145] The perception system 1320 may include several sensors for sensing information about the environment around the vehicle 1300. For example, the perception system 1320 may include a global positioning system (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera.

[0146] The decision control system 1330 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0147] The drive system 1340 may include components that provide powered motion for the vehicle 1300. In one embodiment, the drive system 1340 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, and an air compression engine. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0148] Some or all functions of the vehicle 1300 are controlled by a computing platform 1350. The computing platform 1350 may include at least one processor 1351 and a memory 1352, and the processor 1351 may execute instructions 1353 stored in the memory 1352.

[0149] The processor 1351 may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0150] Memory 1352 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0151] In addition to instructions 1353 , memory 1352 may also store data, such as road maps, route information, and data such as the location, direction, and speed of the vehicle. The data stored in memory 1352 may be used by computing platform 1350 .

[0152] In the embodiment of the present disclosure, the processor 1351 may execute the instruction 1353 to complete all or part of the steps of the above-mentioned method for determining the battery state of charge.

[0153] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable device. The computer program has a code portion for executing the above-mentioned battery state of charge determination method when executed by the programmable device.

[0154] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the present disclosure. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0155] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for determining a battery state of charge, characterized in that: The method comprises: According to the model parameters of the equivalent circuit model of the battery, a state equation and an output equation of the equivalent circuit model are obtained; According to the state equation and the output equation, within a continuous sampling time window, a global optimal algorithm is used to fit the target state parameters of the battery to obtain an initial state of charge of the battery; The current state of charge of the battery is corrected according to the initial state of charge.

2. The method according to claim 1, characterized in that: The equivalent circuit model of the battery includes: an open circuit voltage source, an ohmic internal resistance, a polarization internal resistance and a polarization capacitor; The polarization internal resistance and the polarization capacitor are connected in parallel, and a parallel circuit formed by the polarization internal resistance and the polarization capacitor is connected in parallel with the ohmic internal resistance and the open circuit voltage source in series; The voltage of the open circuit voltage source and the state of charge of the battery have a single mapping relationship.

3. The method according to claim 1, characterized in that The state equation is a description equation of the target state parameter, and the target state parameter includes a vector formed by the state of charge at a sampling point and the polarization current at a sampling point of the battery.

4. The method according to claim 1, characterized in that The output equation is a description equation of the output voltage of the equivalent circuit model.

5. The method according to claim 1, characterized in that The method of fitting the target state parameters of the battery using a global optimal algorithm within a continuous sampling time window according to the state equation and the output equation to obtain the initial state of charge of the battery includes: In the continuous sampling time window, sampling the current and voltage of the battery to obtain a sampling current sequence and a sampling voltage sequence of the battery; According to the sampling current sequence and the output equation, an output voltage sequence of the equivalent circuit model is obtained; According to the sampled voltage sequence and the output voltage sequence, a global optimal algorithm is used to fit the initial state of charge of the equivalent circuit model.

6. The method according to claim 5, characterized in that The step of fitting the initial state of charge of the equivalent circuit model using a global optimal algorithm according to the sampled voltage sequence and the output voltage sequence includes: Obtaining a sum of squares of errors between the sampled voltage sequence and the output voltage sequence; Obtaining the target state parameter that minimizes the sum of squared errors; According to the target state parameter, an initial state of charge of the equivalent circuit model is obtained.

7. The method according to any one of claims 1 to 6, characterized in that The step of fitting the target state parameters of the battery using a global optimal algorithm to obtain the initial state of charge of the battery is performed by a central domain controller of the vehicle.

8. A battery state of charge determination device, characterized in that: include: A first acquisition module, used for acquiring a state equation and an output equation of the equivalent circuit model of the battery according to a model parameter of the equivalent circuit model of the battery; A second acquisition module is used to fit the target state parameters of the battery using a global optimal algorithm within a continuous sampling time window according to the state equation and the output equation to obtain an initial state of charge of the battery; The correction module is used to correct the current state of charge of the battery according to the initial state of charge.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to: execute the executable instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

11. A vehicle, characterized in that: include: The electronic device as claimed in claim 9.

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