A charging control method, system, device and medium for lithium-ion battery

Abstract

The present invention provides a charging control method, system, device and medium for lithium ion batteries, which collect the surface temperature and the current and voltage at both ends of the lithium ion battery to be tested, establish an equivalent circuit model based on an enhanced self-correction model, and add a hysteresis element compared with a common equivalent circuit model, so that the voltage of the circuit can converge to a correct value when the circuit is static or a constant current is input; establish a two-state thermal model to capture the inner core and surface temperature of the battery, which is used to increase constraint conditions and better simulate fault conditions in actual battery applications; couple the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model, so that input is more convenient when state estimation is performed later; combine the electrothermal coupling model with an extended Kalman filter space equation expression, output an internal state estimation value, and use it to obtain a parameter value that cannot be obtained by actual measurement; input the electrothermal coupling model and the internal state estimation value into an MPC model to obtain an optimal charging current with real-time response.

Description

Technical Field

[0001] The present invention belongs to the field of lithium battery energy and optimal charging technology, and specifically relates to a charging control method, system, device and medium for lithium ion batteries. Background Art

[0002] Batteries are used in many different applications, such as electric vehicles. However, batteries often have limitations based on size, capacity, cost, etc., which limit practicality. For example, electric vehicles have limitations based on battery capacity, which may not be acceptable to consumers. Therefore, increasing battery capacity and lifespan can help increase the popularity of electric vehicles and other battery-powered devices.

[0003] When controlling battery charging and discharging, the control loop often has limitations that the battery controller is not aware of. The limitations may be minimum voltage, maximum charge or discharge rate, maximum state of charge, etc. However, when the battery controller seeks to respond to load changes, fast charge conditions, etc., the battery controller will generate control signals that may push the battery to an extreme state, but the constraints will act to keep the battery within the limits. However, constraints are generally nonlinear and can lead to instability in the battery system, which can have undesirable effects. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a charging control method, system, device and medium for a lithium-ion battery, which are used to solve the problem of battery system instability caused by constraint conditions when controlling the charging and discharging of the existing lithium-ion battery.

[0005] The present invention is achieved through the following technical solutions:

[0006] A charging control method for a lithium-ion battery, characterized in that it comprises the following steps:

[0007] S1: Collect the surface temperature, current and voltage of the lithium-ion battery to be tested;

[0008] S2: According to the surface temperature, current and voltage of the lithium-ion battery to be tested, an equivalent circuit model based on the enhanced self-correction model is established;

[0009] S3: According to the surface temperature of the lithium-ion battery to be tested and the current and voltage at both ends, a two-state thermal model is established to capture the internal core and surface temperature of the battery;

[0010] S4: coupling the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model;

[0011] S5: Combine the electrothermal coupling model with the extended Kalman filter space equation expression to output the internal state estimate;

[0012] S6: Input the electrothermal coupling model and the internal state estimation value into the MPC algorithm to obtain the optimal charging current for real-time response.

[0013] Further, the equivalent circuit model includes an open circuit voltage Vocv, and the positive electrode of the open circuit voltage Vocv is sequentially connected to a hysteresis element hyst, an RC circuit and a resistor R0;

[0014] The RC circuit includes a polarized capacitor C1 and a polarized internal resistor R1 connected in parallel;

[0015] The SOC is z(t). If the battery is fully charged, the SOC is z(t)=100%. If the battery is fully discharged, the SOC is z(t)=0%.

[0016] Furthermore, the discrete time and hysteresis voltage of the hysteresis state are:

[0017]

[0018] v h,k =Mh k ;

[0019] Where, the total battery capacity is Q, the current is i(t), the sampling time is Δt, the efficiency factor is η(t), sgn[i k ] is input i k The sign of γ is a positive unitless constant, M is the maximum hysteresis polarization voltage, the hysteresis state is unitless, and -1≤h k ≤1;

[0020] The output voltage of the equivalent circuit is:

[0021]

[0022] Among them, M0 is the instantaneous voltage;

[0023] The equivalent circuit model is:

[0024]

[0025] Among them, A RC ,B RC and A H,k The definition is as follows:

[0026]

[0027]

[0028]

[0029] Further, the two-state thermal model is:

[0030]

[0031]

[0032] Among them, T s is the surface temperature, T c is the core temperature, T f is the coolant flow temperature, Q is the heat generated by the battery cell, R c is the thermal resistance, R u Convective resistance simulated for heat exchange.

[0033] Furthermore, the electrothermal coupling between the equivalent circuit model and the two-state thermal model is performed through heat Q, and the expression of Q in discrete time is:

[0034]

[0035] Among them, i k is the circuit current at the kth moment, y k is the output voltage of the equivalent circuit at the kth moment, OCV k is the open circuit voltage at the kth moment, T c,k is the core temperature at the kth moment.

[0036] Further, in step S5, a state transfer equation is established to connect the state of the model at the previous moment and the current moment, and then an observation equation is established to connect the model measurement value and the state value;

[0037] Predict the current state based on the estimated state value at the previous moment and the circuit model;

[0038] Based on the Jacobian matrix at the previous round of estimated values ​​and the current round of state prediction values, the error covariance and Kalman gain matrix are obtained;

[0039] Update the state estimation measurement and error covariance based on the gain matrix;

[0040] The parameter values ​​measured by the equivalent circuit model are input in real time, and the results are updated in real time.

[0041] Furthermore, the optimal charging current is:

[0042]

[0043] i k+1 =i k +Δi k+1 ;

[0044] Among them, Δi k+1is the change in current between the kth moment and the k+1th moment, ρ is the weight factor, φ z and G z is the control matrix calculated using the A, B and C matrices of the state equation, R s is the optimization target vector matrix.

[0045] A charging control system for a lithium-ion battery, comprising:

[0046] An equivalent circuit model building unit, used for building an equivalent circuit model based on an enhanced self-correction model;

[0047] A two-state thermal modeling unit to capture the battery’s core and surface temperatures;

[0048] An electrothermal coupling model building unit is used to couple the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model;

[0049] An internal state estimation value output unit is used to combine the electrothermal coupling model with the extended Kalman filter space equation expression to output the internal state estimation value;

[0050] The optimal charging current unit inputs the electrothermal coupling model and the internal state estimation value into the MPC model to obtain the optimal charging current for real-time response.

[0051] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of a charging control method for a lithium-ion battery are implemented.

[0052] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of a charging control method for a lithium-ion battery.

[0053] Compared with the prior art, the present invention has the following beneficial technical effects:

[0054] The present invention provides a charging control method, system, device and medium for lithium-ion batteries. The surface temperature and the current and voltage at both ends of the lithium-ion battery to be tested are collected, and an equivalent circuit model based on an enhanced self-correction model is established. Compared with the ordinary equivalent circuit model, a hysteresis element is added, so that the voltage of the circuit can converge to a correct value when the circuit is stationary or a constant current is input; a two-state thermal model is established to capture the inner core and surface temperature of the battery, which is used to increase constraints and better simulate fault conditions in actual battery applications; the equivalent circuit model and the two-state thermal model are coupled to obtain an electrothermal coupling model, which makes input more convenient when performing state estimation later; the electrothermal coupling model is combined with an extended Kalman filter space equation expression to output an internal state estimation value, which is used to obtain a parameter value that cannot be obtained by actual measurement; the electrothermal coupling model and the internal state estimation value are input into an MPC model to obtain an optimal charging current for real-time response, thereby improving charging stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a flow chart of a charging control method for a lithium-ion battery in a specific embodiment of the present invention;

[0056] Figure 2 It is an equivalent circuit diagram in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0057] The present invention is further described in detail below in conjunction with specific embodiments, which are intended to explain the present invention rather than to limit it.

[0058] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only embodiments of a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0059] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0060] The present invention provides a charging control method for a lithium ion battery, such as Figure 1 As shown, the following steps are included:

[0061] S2: Establish an equivalent circuit model based on the enhanced self-correction model;

[0062] S3: Establish a two-state thermal model to capture the battery’s core and surface temperatures;

[0063] S4: coupling the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model;

[0064] S5: Combine the electrothermal coupling model with the extended Kalman filter space equation expression to output the internal state estimate;

[0065] S6: Input the electrothermal coupling model and the internal state estimation value into the MPC model to obtain the optimal charging current for real-time response.

[0066] Preferably, Figure 2 As shown, the equivalent circuit model includes an open circuit voltage Vocv, and the positive electrode of the open circuit voltage Vocv is sequentially connected to a hysteresis element hyst, an RC circuit and a resistor R0;

[0067] The RC circuit includes a polarized capacitor C1 and a polarized internal resistor R1 connected in parallel;

[0068] The SOC is z(t). If the battery is fully charged, the SOC is z(t)=100%. If the battery is fully discharged, the SOC is z(t)=0%.

[0069] Furthermore, the discretization time of the RC circuit and the polarization voltage is:

[0070]

[0071] v h,k =Mh k ;

[0072] Where, the total battery capacity is Q, the current is i(t), the sampling time is Δt, the efficiency factor is η(t), sgn[i k ] is input i k The sign of γ is a positive unitless constant, M is the maximum hysteresis polarization voltage, the hysteresis state is unitless, and -1≤h k ≤1;

[0073] The output voltage of the equivalent circuit is:

[0074]

[0075] Among them, M0 is the instantaneous voltage;

[0076] The equivalent circuit model is:

[0077]

[0078] Among them, A RC ,B RC and A H,k The definition is as follows:

[0079]

[0080]

[0081]

[0082] Preferably, the two-state thermal model is:

[0083]

[0084]

[0085] Among them, T s is the surface temperature, T c is the core temperature, T f is the coolant flow temperature, Q is the heat generated by the battery cell, R c is the thermal resistance, R u Convective resistance simulated for heat exchange.

[0086] Preferably, the electrothermal coupling between the equivalent circuit model and the two-state thermal model is performed via heat Q, and the discrete time of Q is:

[0087]

[0088] Among them, i k is the circuit current at the kth moment, y k is the output voltage of the equivalent circuit at the kth moment, OCVk is the open circuit voltage at the kth moment, T c,k is the core temperature at the kth moment.

[0089] Preferably, in step S5, a state transfer equation is established to connect the state of the model at the previous moment and the current moment, and then an observation equation is established to connect the model measurement value and the state value;

[0090] Predict the current state based on the estimated state value at the previous moment and the circuit model;

[0091] Based on the Jacobian matrix at the previous round of estimated values ​​and the current round of state prediction values, the error covariance and Kalman gain matrix are obtained;

[0092] Update the state estimation measurement and error covariance based on the gain matrix;

[0093] The parameter values ​​measured by the equivalent circuit model are input in real time, and the results are updated in real time.

[0094] Specifically, it is necessary to first establish an extended Kalman filter state space equation, which is:

[0095] x k =A k-1 x k-1 +B k-1 u k-1 +ω k

[0096] z k =C k x k +D k u k +v k

[0097] In the formula, u k-1 is the input of the system at the k-1th moment, x k is the state quantity of the system at the kth moment, z k is the output of the system at the kth moment, ω k is the current measurement error, v k is an uncorrelated white Gaussian random process with zero mean and covariance matrix;

[0098] Update the forecast error covariance time:

[0099]

[0100]

[0101] A k-1 and B k-1are the last estimated values ​​x of function f(x) and h(x) respectively. k-1 and the predicted value x of this round of state k The Jacobian matrix at , and then the predicted covariance can be obtained as:

[0102]

[0103] The output is estimated by assuming that x k and noise v k is the best approximation to estimate the system output:

[0104] z k =h k (x k ,u k ,v k )

[0105] Linearize the error to get:

[0106] z k ≈C k x k +D k v k ;

[0107] in:

[0108]

[0109]

[0110] The gain matrix is ​​obtained as:

[0111]

[0112] Update the state estimation measurement: Based on the gain matrix and the new model state value obtained, estimate the state:

[0113] x k = x′ k +M k (z k -h(x′ k ));

[0114] Update the error covariance measure:

[0115]

[0116] The parameter values ​​obtained by measuring the electrothermal coupling model are input into the extended Kalman filter state and observation equations for prediction:

[0117] First write the equation for the state of charge SOC:

[0118]

[0119] Among them, z k is the SOC at the kth moment, i k is the battery current at the kth moment, Q is the rated capacity of the battery;

[0120] For z k+1 The partial derivative at the true value of the previous point is:

[0121]

[0122]

[0123] The maximum polarization voltage of the battery caused by the hysteresis effect is:

[0124]

[0125] Where γ is a positive constant used to adjust the decay rate, which makes the equation stable during both charging and discharging.

[0126] By setting θ = e^(-Δt / (R j C j )), the above formula can be transformed into:

[0127]

[0128] Right now:

[0129]

[0130] The hysteresis state equation A matrix is:

[0131]

[0132]

[0133] Taking partial derivatives of the output equations of the equivalent circuit model of the lithium battery, we can get:

[0134]

[0135] The first three items determine the C array, and the fourth item determines the D array. Substituting the measured data into the calculation, the output voltage value can be obtained;

[0136] Due to the current sensor measurement error, the state equation of the battery core temperature is updated as follows:

[0137]

[0138] Due to the measurement error of the temperature sensor, the state equation of the battery surface temperature is updated as follows:

[0139]

[0140] By substituting the actual measured values, the temperature of the battery core and the battery surface that cannot be measured can be obtained.

[0141] Preferably, the principle of the MPC model predicting the input state space equation is as follows:

[0142] Make appropriate changes to the state equation and replace x k Set to [x k u k ] T :

[0143] X k+1 =A'X k +B'Δu k+1

[0144] z k =C'X k

[0145] in:

[0146] C'=[CD],Δu k+1 =u k+1 -u k ;

[0147] The objective function is given by:

[0148]

[0149] The governing equation for predicting the current is as follows:

[0150] X k+1 =A'X k +B'Δu k+1 ;

[0151] X k+2 =A' 2 X k +A'B'Δu k+1 +B'Δu k+2 ;

[0152]

[0153] Correspondingly, the prediction output equation is as follows:

[0154] z k+1 =C'A'X k+1 +C'B'Δu k+1 ;

[0155] z k+2 =C'A'2 X k+1 +C'A'B'Δu k+1 +C'B'Δu k+2 ;

[0156]

[0157] The above formula is abbreviated into a matrix:

[0158]

[0159] in:

[0160]

[0161]

[0162]

[0163] The objective function is transformed into:

[0164]

[0165] In order to obtain the required optimal control solution, it is necessary to find the partial derivative of the objective function with respect to the control quantity and set the partial derivative value equal to zero. The solution obtained is the optimal solution of the model predictive control.

[0166]

[0167] Considering the limitation of charging current, i min ≤i k ≤i max , written in matrix form as follows:

[0168] MΔi k+1 ≤γ;

[0169] in,

[0170]

[0171] M is a lower triangular matrix filled with 1s;

[0172] Considering the limitation of charging voltage, v min ≤v k ≤v max , written in matrix form as follows:

[0173] y vk+1 =φ v χ k +G v Δi k+1 ;

[0174] in,

[0175]

[0176] Considering the temperature limit of the battery core, T c,min ≤T c,k ≤T c,max , written in matrix form as follows:

[0177]

[0178] in,

[0179]

[0180] The optimal charging current can be calculated, and ρ is defined as the weighting factor. The formula is as follows:

[0181]

[0182] i k+1 =i k +Δi k+1 ;

[0183] The present invention provides a charging control system for a lithium-ion battery, comprising

[0184] An equivalent circuit model building unit, used for building an equivalent circuit model based on an enhanced self-correction model;

[0185] A two-state thermal modeling unit to capture the battery’s core and surface temperatures;

[0186] An electrothermal coupling model building unit is used to couple the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model;

[0187] An internal state estimation value output unit is used to combine the electrothermal coupling model with the extended Kalman filter space equation expression to output the internal state estimation value;

[0188] The optimal charging current unit inputs the electrothermal coupling model and the internal state estimation value into the MPC model to obtain the optimal charging current for real-time response.

[0189] In another embodiment of the present invention, a computer device is provided, the computer device comprising a processor and a memory, the memory being used to store a computer program, the computer program comprising program instructions, and the processor being used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions in a computer storage medium to implement a corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of a charging control method for a lithium-ion battery.

[0190] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of a charging control method for a lithium-ion battery in the above embodiment.

[0191] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0192] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0193] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0194] These computer program instructions can also be loaded into a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing one or more processes and / or blocks in the flowchart. Figure 1 A step that specifies a function in one or more boxes.

[0195] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A charging control method for a lithium-ion battery, characterized in that: The following steps are involved: S1: Collect the surface temperature, current and voltage of the lithium-ion battery to be tested; S2: According to the surface temperature, current and voltage of the lithium-ion battery to be tested, an equivalent circuit model based on the enhanced self-correction model is established; S3: According to the surface temperature of the lithium-ion battery to be tested and the current and voltage at both ends, a two-state thermal model is established to capture the inner core and surface temperature of the battery; S4: coupling the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model; S5: Combine the electrothermal coupling model with the extended Kalman filter space equation expression to output the internal state estimate; S6: Input the electrothermal coupling model and the internal state estimation value into the MPC algorithm to obtain the optimal charging current for real-time response; The equivalent circuit model includes an open circuit voltage Vocv, and the positive electrode of the open circuit voltage Vocv is sequentially connected to a hysteresis element hyst, an RC circuit and a resistor R0; The RC circuit includes a polarized capacitor C1 and a polarized internal resistor R1 connected in parallel; The state of charge SOC of a lithium-ion battery is z(t). If the battery is fully charged, the state of charge SOC of the lithium-ion battery is z(t)=100%. If the battery is fully discharged, the state of charge SOC of the lithium-ion battery is z(t)=0%. The discrete time and hysteresis voltage of the hysteresis state of the hysteresis element hyst are: v h,k =Mh k ; Among them, the total battery capacity is Q, the current is i(t), the sampling time is Δt, the efficiency factor is η(t), sgn[i k ] is input i k The sign of γ is a positive unitless constant, M is the maximum hysteresis polarization voltage, the hysteresis state is unitless, and -1≤h k ≤1; The output voltage of the equivalent circuit is: Among them, M0 is the instantaneous voltage; The equivalent circuit model is: Among them, A RC ,B RC and A H,k The definition is as follows:

2. A charging control method for a lithium-ion battery according to claim 1, characterized in that: The two-state thermal model is: Among them, T s is the surface temperature, T c is the core temperature, T f is the coolant flow temperature, Q is the heat generated by the battery cell, R c is the thermal resistance, R u Convective resistance simulated for heat exchange.

3. A charging control method for a lithium-ion battery according to claim 1, characterized in that: The electrothermal coupling between the equivalent circuit model and the two-state thermal model is carried out through the heat Q, and the expression of Q in discrete time is: Among them, i k is the circuit current at the kth moment, y k is the output voltage of the equivalent circuit at the kth moment, OCV k is the open circuit voltage at the kth moment, T c,k is the core temperature at the kth moment.

4. A charging control method for a lithium-ion battery according to claim 1, characterized in that: In step S5, a state transfer equation is established to connect the state of the model at the previous moment and the current moment, and then an observation equation is established to connect the model measurement value and the state value; Predict the current state based on the estimated state value at the previous moment and the circuit model; Based on the Jacobian matrix at the previous round of estimated values ​​and the current round of state prediction values, the error covariance and Kalman gain matrix are obtained; Update the state estimation measurement and error covariance based on the gain matrix; The parameter values ​​measured by the equivalent circuit model are input in real time, and the results are updated in real time.

5. A charging control method for a lithium-ion battery according to claim 1, characterized in that: The optimal charging current is: i k+1 =i k +Δi k+1 ; Among them, Δi k+1 is the change in current between the kth moment and the k+1th moment, ρ is the weight factor, φ z and G z is the control matrix calculated using the A, B and C matrices of the state equation, R s is the optimization target vector matrix.

6. A charging control system for a lithium-ion battery, characterized in that: A charging control method for a lithium-ion battery according to any one of claims 1 to 5, comprising: An equivalent circuit model building unit, used for building an equivalent circuit model based on an enhanced self-correction model; A two-state thermal modeling unit to capture the battery’s core and surface temperatures; An electrothermal coupling model building unit is used to couple the equivalent circuit model and the two-state thermal model to obtain an electrothermal coupling model; An internal state estimation value output unit is used to combine the electrothermal coupling model with the extended Kalman filter space equation expression to output the internal state estimation value; The optimal charging current unit inputs the electrothermal coupling model and the internal state estimation value into the MPC model to obtain the optimal charging current for real-time response.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the charging control method for a lithium-ion battery as claimed in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the charging control method for a lithium-ion battery as claimed in any one of claims 1 to 5 are implemented.

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