Battery thermal management method and device, electronic equipment and storage medium

Abstract

The invention provides a battery thermal management method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring battery operation data, related to the temperature change rate, of a battery and target data of a thermal management system; performing state prediction of the thermal management system based on battery operation data and target data to obtain a state control sequence within a time period of reaching the target moment; the state control sequence comprises the inlet target temperature of each control moment in the time period; the inlet target temperature is the temperature of the cooling liquid at the inlet of the cooling liquid circulating pipeline at the target moment, and the cooling liquid circulating pipeline is a circulating pipeline of the cooling liquid which exchanges heat with the battery in the thermal management system; and based on the state control sequence, controlling the temperature of the cooling liquid at the inlet of the cooling liquid circulating pipeline at each control moment, so that the control capability of the thermal management system on the aspects of energy consumption, temperature and time is optimal.

Description

Technical Field

[0001] The present disclosure relates to the technical field of battery thermal management, and in particular to a battery thermal management method and device, an electronic device, and a storage medium. Background Art

[0002] The performance of electric vehicle batteries is closely related to their operating temperature. Therefore, to ensure battery performance, electric vehicles must operate at an appropriate temperature. Related technologies utilize thermal management systems to control battery cooling using water or other coolants. These strategies aim to minimize the difference between the battery temperature and the target temperature and optimize the energy consumption of the thermal management system's actuators. These strategies determine the optimal output speeds for the water pump and fan in cooling mode.

[0003] However, in the related art, when the thermal management system is controlled according to the optimal output speeds of the water pump and the fan in the thermal management system, the control accuracy of the thermal management system is insufficient. Summary of the Invention

[0004] The present disclosure provides a battery thermal management method and device, an electronic device, and a storage medium.

[0005] According to a first aspect of the present disclosure, a battery thermal management method is provided, comprising:

[0006] Obtaining battery operating data related to the battery's temperature change rate and target data of the thermal management system; wherein the battery operating data includes the battery's real-time temperature, and the target data includes the battery's target temperature; the battery target temperature is the temperature that the battery needs to reach at the target time;

[0007] The state of the thermal management system is predicted based on the battery operating data and the target data to obtain a state control sequence within a time period to reach the target time. The state control sequence includes the inlet target temperature at each control time within the time period. The inlet target temperature is the temperature of the coolant at the inlet of the coolant circulation pipe at the target time. The coolant circulation pipe is the circulation pipe of the coolant in the thermal management system that exchanges heat with the battery.

[0008] Based on the state control sequence, the temperature of the coolant at the inlet of the coolant circulation pipeline is controlled at each control moment, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized.

[0009] In one embodiment, the battery operation data further includes real-time inlet temperature, real-time outlet temperature, real-time coolant flow rate, real-time vehicle speed, real-time battery current, and real-time ambient temperature;

[0010] The state control sequence also includes thermal management enablement at each control moment within the time period;

[0011] Based on the battery operation data and target data, the state of the thermal management system is predicted to obtain the state control sequence within the time period to reach the target time, including:

[0012] The battery operation data is used as the state parameter, the inlet target temperature and the thermal management enable are used as the control parameters. Based on the state parameters and the control parameters, the optimization goal is to achieve the optimal control capability of the thermal management system in terms of energy consumption, temperature and time. The inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period are solved.

[0013] In one embodiment, a state prediction of a thermal management system is performed based on battery operation data and target temperature data to obtain a state control sequence within a time period to reach the target time, including:

[0014] Substitute state parameters and control parameters into the pre-built state space model;

[0015] Within the preset constraints, with the goal of minimizing a preset cost function, the state space model is solved to obtain the inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period; wherein the cost function refers to the objective function used to optimize the control capability of the thermal management system in terms of energy consumption, temperature and time.

[0016] In one embodiment, the cost function includes a control energy consumption item cost function, a battery temperature control accuracy item cost function, an inlet temperature control accuracy item cost function, and a time control accuracy item cost function;

[0017] The cost function of the control energy consumption term is constructed based on the state control sequence corresponding to each control moment in the time period up to the last moment of state prediction;

[0018] The cost function of the battery temperature control accuracy term is constructed based on the battery real-time temperature and the battery target temperature at the last moment;

[0019] The cost function of the inlet temperature control accuracy term is constructed based on the inlet real-time temperature and the inlet target temperature at the last moment;

[0020] The time control accuracy cost function is constructed based on the last moment and the target moment.

[0021] In one embodiment,

[0022] The control energy consumption cost function refers to the product value of the cumulative sum of the state control sequence corresponding to each control moment in the time period reaching the last moment of the state prediction and the first weight;

[0023] The cost function of the battery temperature control accuracy term refers to the product value of the first difference between the battery real-time temperature at the last moment and the battery target temperature and the second weight;

[0024] The cost function of the inlet temperature control accuracy term refers to the product value of the second difference between the inlet real-time temperature and the inlet target temperature at the last moment and the third weight;

[0025] The time control accuracy cost function refers to the product of the third difference between the last moment and the target moment and the fourth weight;

[0026] The cost function refers to the sum of the cost function of the control energy consumption item, the cost function of the battery temperature control accuracy item, the cost function of the inlet temperature control accuracy item and the cost function of the time control accuracy item.

[0027] In one embodiment, the constraints are:

[0028] Thermal management enable is a first preset value or a second preset value; wherein the first preset value indicates that thermal management enable is not enabled, and the second preset value indicates that thermal management enable is enabled;

[0029] The inlet target temperature is between a first preset temperature and a second preset temperature; wherein the first preset temperature is lower than the second preset temperature.

[0030] In one embodiment,

[0031] The obtaining of battery operation data related to the temperature change rate of the battery includes:

[0032] The battery real-time temperature, battery target temperature, inlet real-time temperature, outlet real-time temperature and coolant real-time flow rate are obtained from the thermal management system, and the vehicle real-time speed and ambient real-time temperature are obtained from the vehicle controller, and the battery real-time current is obtained from the battery management unit.

[0033] According to a second aspect of the present disclosure, a battery thermal management device is provided, comprising:

[0034] an acquisition unit, configured to acquire battery operating data related to a temperature change rate of the battery and target data of a thermal management system; wherein the battery operating data includes the real-time temperature of the battery, and the target data includes the target battery temperature of the battery; the target battery temperature is the temperature that the battery needs to reach at a target time;

[0035] a prediction unit for predicting the state of the thermal management system based on the battery operating data and the target data, and obtaining a state control sequence within a time period leading to a target moment; the state control sequence includes an inlet target temperature at each control moment within the time period; the inlet target temperature is the temperature of the coolant at the inlet of a coolant circulation pipe at the target moment; the coolant circulation pipe is a circulation pipe for the coolant in the thermal management system that exchanges heat with the battery;

[0036] The control unit is used to control the temperature of the coolant at the inlet of the coolant circulation pipeline at each control moment based on the state control sequence, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized.

[0037] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0038] at least one processor; and

[0039] a memory communicatively connected to at least one processor; wherein,

[0040] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of the first aspect.

[0041] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute the method of the aforementioned first aspect.

[0042] The present disclosure provides a battery thermal management method and device, electronic device, and storage medium. The method provided by the present disclosure includes: obtaining battery operating data related to the temperature change rate of the battery and target data of the thermal management system; wherein the battery operating data includes the real-time battery temperature, and the target data includes the battery target temperature of the battery; the battery target temperature is the temperature that the battery needs to reach at the target time; based on the battery operating data and the target data, the state of the thermal management system is predicted to obtain a state control sequence within a time period to reach the target time; the state control sequence includes the inlet target temperature at each control time within the time period; the inlet target temperature is the temperature of the coolant at the inlet of the coolant circulation pipe at the target time, the coolant circulation pipe being a circulation pipe for the coolant in the thermal management system that performs heat exchange with the battery; based on the state control sequence, the temperature of the coolant at the inlet of the coolant circulation pipe is controlled at each control time to optimize the control capability of the thermal management system in terms of energy consumption, temperature, and time.

[0043] According to the solution disclosed herein, by predicting the state of the thermal management system based on the battery operating data including the real-time battery temperature and the target data of the thermal management system including the target battery temperature, the inlet target temperature at each control moment within the time period for reaching the target moment is obtained, and then the temperature of the coolant at the inlet of the coolant circulation pipeline is accurately controlled at each control moment, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized, thereby improving the control accuracy of the thermal management system.

[0044] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0046] Figure 1 A schematic flow chart of a battery thermal management method provided in an embodiment of the present disclosure;

[0047] Figure 2 A schematic structural diagram of a battery thermal management device provided in an embodiment of the present disclosure;

[0048] Figure 3 A schematic block diagram of an example electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0049] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0050] In order to facilitate those skilled in the art to better understand the technical solutions described in the embodiments of the present disclosure, the technical terms in the embodiments of the present disclosure are explained as follows before introducing the embodiments of the present disclosure.

[0051] Model Predictive Control (MPC): This method predicts the future state of a system based on its current state and optimizes the prediction model of the control signal within each control cycle.

[0052] The following describes a battery thermal management method and apparatus, an electronic device, and a storage medium according to embodiments of the present disclosure with reference to the accompanying drawings.

[0053] The performance of electric vehicle batteries is closely related to their operating temperature. Therefore, to ensure optimal battery performance, electric vehicle batteries must operate at an appropriate temperature. Thermal management systems are commonly used to regulate battery temperature by injecting water or other coolant at a specific temperature into the inlet of the battery's coolant circulation pipe.

[0054] Based on this, an embodiment of the present disclosure provides a battery thermal management method.

[0055] The battery thermal management method provided by this disclosure can be applied to vehicles equipped with an MPC controller. Accordingly, the method can be executed by the MPC controller or other control devices such as the vehicle's vehicle controller. The following description uses the MPC controller as an example.

[0056] like Figure 1 As shown, the battery thermal management method provided by the embodiment of the present disclosure includes the following steps:

[0057] Step 101, obtaining battery operation data related to the temperature change rate of the battery and target data of the thermal management system;

[0058] In one embodiment, the battery operation data of the battery includes the real-time temperature of the battery.

[0059] In one embodiment, the target data of the thermal management system includes a target battery temperature of the battery; the target battery temperature is the temperature that the battery needs to reach at a target time.

[0060] In one embodiment, the real-time temperature of the battery is expressed as T batt Indicates that the battery target temperature is T batt,target express.

[0061] In one embodiment, the battery operation data related to the temperature change rate of the battery also includes other data, such as the real-time temperature T at the inlet of the battery coolant circulation pipe. inwtr , outlet real-time temperature T outwtr wait.

[0062] Step 102 , predicting the state of the thermal management system based on the battery operation data and the target data, and obtaining a state control sequence within a time period to reach the target time;

[0063] In one embodiment, the state control sequence includes the inlet target temperature at each control moment within the time period.

[0064] In one embodiment, the inlet target temperature is expressed as T inwtr,target express.

[0065] In one embodiment, the inlet target temperature is the temperature of the coolant at the inlet of the coolant circulation pipe at the target time, and the coolant circulation pipe is a circulation pipe of the coolant in the thermal management system that performs heat exchange with the battery.

[0066] In one embodiment, a state space model can be used to take battery operation data as system state parameters of the thermal management system, and control parameters included in the state control sequence, such as the inlet target temperature, as control parameters for state prediction to obtain a state control sequence within the time period of reaching the target moment.

[0067] In one embodiment, a Markov model or a hidden Markov model can also be used, with battery operating data as observable values ​​of the thermal management system and the battery target temperature as an implicit state. The Markov model is solved to obtain a state control sequence within the time period to reach the target moment.

[0068] In one embodiment, the state-space model may adopt an MPC-based state-space model.

[0069] Step 103 , based on the state control sequence, controls the temperature of the coolant at the inlet of the coolant circulation pipe at each control moment, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized.

[0070] In one embodiment, since the state control sequence includes the inlet target temperature at each control moment within the time period, the MPC controller can control the inlet real-time temperature at each control moment to be equal to the inlet target temperature through the actuator of the thermal management system.

[0071] In one embodiment, based on a state control sequence, the temperature of the coolant at the inlet of the coolant circulation pipe is controlled at each control moment, which can optimize the control capabilities of the thermal management system in terms of energy consumption, temperature and time, and effectively improve the control accuracy of the thermal management system.

[0072] The present disclosure provides a battery thermal management method and device, electronic device, and storage medium. The method provided by the present disclosure includes: obtaining battery operating data related to the temperature change rate of the battery and target data of the thermal management system; wherein the battery operating data includes the real-time battery temperature, and the target data includes the battery target temperature of the battery; the battery target temperature is the temperature that the battery needs to reach at the target time; based on the battery operating data and the target data, the state of the thermal management system is predicted to obtain a state control sequence within a time period for reaching the target time; the state control sequence includes the inlet target temperature at each control time within the time period; the inlet target temperature is the temperature of the coolant at the inlet of the coolant circulation pipe at the target time, the coolant circulation pipe being a circulation pipe for the coolant in the thermal management system that performs heat exchange with the battery; based on the state control sequence, the temperature of the coolant at the inlet of the coolant circulation pipe is controlled at each control time to optimize the control capability of the thermal management system in terms of energy consumption, temperature, and time.

[0073] According to the solution disclosed herein, by predicting the state of the thermal management system based on the battery operating data including the real-time battery temperature and the target data of the thermal management system including the target battery temperature, the inlet target temperature at each control moment within the time period for reaching the target moment is obtained, and then the temperature of the coolant at the inlet of the coolant circulation pipeline is accurately controlled at each control moment, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized, thereby improving the control accuracy of the thermal management system.

[0074] In one embodiment, the battery operation data related to the temperature change rate of the battery also includes other data, such as the inlet and outlet temperatures of the battery's coolant circulation pipe, the coolant flow rate, the vehicle speed, the ambient temperature, etc.

[0075] Based on this, in one embodiment, the battery operation data also includes the inlet real-time temperature T inwtr , outlet real-time temperature T outwtr , coolant real-time flow rate V wtr , vehicle real-time speed V car , battery real-time current I and ambient real-time temperature T air .

[0076] In one embodiment, the inlet real-time temperature T inwtr Refers to the temperature of the coolant at the inlet of the coolant circulation pipe flowing into the battery when the thermal management system is turned on.

[0077] In one embodiment, the outlet real-time temperature T outwtr It refers to the temperature of the coolant at the outlet of the battery's coolant circulation pipe after the coolant absorbs the battery's heat during battery use.

[0078] In one embodiment, at the target time, the inlet real-time temperature Tinwtr and the battery target temperature T batt,target The thermal management system is not turned on at this time.

[0079] In one embodiment, the battery operation data also includes parameters associated with the battery temperature change rate, such as the cooling pipe diameter, battery power, and battery charge and discharge status.

[0080] In one embodiment, the diameter of the cooling pipe refers to the diameter of the coolant circulation pipe.

[0081] In one embodiment, the state control sequence of the thermal management system is not only related to the inlet target temperature, but also to whether the thermal management system is turned on.

[0082] Based on this, in one embodiment, the state control sequence further includes data related to the energy consumption of the actuator, such as the thermal management enable Q at each control moment within a time period.

[0083] In one embodiment, the thermal management enable Q is equal to 0, indicating that the thermal management system is not enabled and the control energy consumption is low; the thermal management enable Q is equal to 1, indicating that the thermal management system is enabled and the control energy consumption is high. Of course, the thermal management enable Q can also be two other different values ​​to indicate whether the thermal management system is enabled.

[0084] In one embodiment, the control sequence may further include a coolant inlet rate at each control moment within a time period; the coolant inlet rate refers to the coolant flow rate at the inlet of the coolant circulation pipeline, and the coolant inlet rate is strongly correlated with the battery temperature change rate; specifically, increasing the coolant inlet rate can increase the battery temperature change rate, and conversely, decreasing the battery temperature change rate.

[0085] Accordingly, based on the above battery operation data and state control sequence, step 102 includes:

[0086] The battery operating data is used as the state parameter, and the inlet target temperature and thermal management enable are used as control parameters. Based on the state parameters and control parameters, the optimization goal is to achieve the optimal control capability of the thermal management system in terms of energy consumption, temperature and time. The inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period are solved.

[0087] In one embodiment, a state space model can be used to convert the real-time battery temperature T batt , real-time inlet temperature T inwtr , outlet real-time temperature T outwtr , coolant real-time flow rate V wtr , vehicle real-time speed V car , battery real-time current I and ambient real-time temperature T airAs the system state parameters of the thermal management system, the control parameters contained in the state control control sequence, such as the inlet target temperature T inwtr,target The thermal management enable Q is used as the control parameter to predict the state and obtain the inlet target temperature T at each control moment within the time period to reach the target moment. inwtr,target And the thermal management enable Q at each control moment in the time period.

[0088] The present disclosure utilizes a state space model, takes battery operating data as a state parameter, that is, system input, and takes the battery target temperature as the system output, and then takes minimizing the difference between the battery's real-time temperature at the target moment and the battery target temperature, and optimizing the energy consumption of the thermal management system actuator as the optimization goal. It can solve the inlet target temperature at each control moment within the time period and the thermal management enable at each control moment within the time period, thereby improving the control accuracy of the thermal management system and effectively reducing energy consumption.

[0089] In one embodiment, if the state-space model is an MPC-based state-space model, step 102 includes:

[0090] Substitute state parameters and control parameters into the pre-built state space model;

[0091] In one embodiment, the pre-built state-space model refers to a trained state-space model.

[0092] In one embodiment, in the trained state-space model, the state matrix and the control matrix are known.

[0093] In one embodiment, the state matrix is ​​used to represent the probability of the current system state transitioning to another system state. For example, if the current real-time battery temperature is 20 degrees Celsius, and the real-time battery temperature in other system states is 19 degrees Celsius or 21 degrees Celsius, the state matrix represents the probability of the real-time battery temperature changing from 20 degrees Celsius to 19 degrees Celsius, or from 20 degrees Celsius to 21 degrees Celsius.

[0094] In one embodiment, the MPC-based state space model can be expressed by the following mathematical expression:

[0095] x(k+1)=Ax(k)+B u u(k);

[0096] Among them, x(k) is the system state variable associated with the system state, that is, the state parameter, A is the state matrix, u(k) is the control input variable associated with the system state, that is, the control parameter, B u is the control matrix.

[0097] Within the preset constraints, with the goal of minimizing the preset cost function, the state space model is solved to obtain the inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period.

[0098] In one embodiment, the cost function refers to an objective function for optimizing the control capability of the thermal management system in terms of energy consumption, temperature and time.

[0099] The present disclosure uses an MPC-based state space model to substitute state parameters and control parameters into a pre-constructed state space model, and then solves the state space model within preset constraints with the goal of minimizing a preset cost function. This can solve the inlet target temperature at each control moment in a time period and the thermal management enable at each control moment in the time period, thereby improving the control accuracy of the thermal management system and effectively reducing energy consumption.

[0100] In one embodiment, the cost function includes a control energy consumption item cost function, a battery temperature control accuracy item cost function, an inlet temperature control accuracy item cost function, and a time control accuracy item cost function;

[0101] The cost function of the control energy consumption term is constructed based on the state control sequence corresponding to each control moment in the time period up to the last moment of state prediction;

[0102] In one embodiment, the final time of state prediction refers to the time when the difference between the real-time battery temperature and the target battery temperature, as predicted by the state-space model, is minimized and the energy consumption of the thermal management system's actuators is minimized. The final time may be greater than or less than the target time. Because the state-space model is solved for the optimal solution, the final time is typically less than the target time.

[0103] In one embodiment, the last time can be represented by (k+t).

[0104] In one embodiment, the state control sequence corresponding to each control moment can be represented by u(k+i).

[0105] In one embodiment, the control energy consumption cost function is associated with the control energy consumption of the actuator of the thermal management system.

[0106] The cost function of the battery temperature control accuracy term is constructed based on the battery real-time temperature and the battery target temperature at the last moment;

[0107] In one embodiment, the real-time temperature of the battery at the last moment can be expressed as T batt (k+t) represents.

[0108] In one embodiment, the battery temperature control accuracy cost function is associated with the battery temperature control accuracy.

[0109] The cost function of the inlet temperature control accuracy term is constructed based on the inlet real-time temperature and the inlet target temperature at the last moment;

[0110] In one embodiment, the inlet real-time temperature at the last moment can be expressed as T inwtr (k+t) represents.

[0111] In one embodiment, the inlet temperature control accuracy cost function is associated with the control accuracy of the inlet temperature of the coolant circulation pipe of the battery.

[0112] The time control accuracy cost function is constructed based on the last moment and the target moment.

[0113] In one embodiment, the time control accuracy cost function is associated with the control accuracy at the target time.

[0114] The cost function constructed by the present invention includes a cost function for controlling energy consumption, a cost function for controlling battery temperature accuracy, a cost function for controlling inlet temperature accuracy, and a cost function for controlling time accuracy. The cost function constructed by the present invention can accurately calculate the control accuracy of control energy consumption, battery temperature control accuracy, inlet temperature control accuracy, and time control accuracy at each control moment within a time period. Furthermore, by utilizing the cost function constructed by the present invention, a more accurate inlet target temperature at each control moment within a time period and thermal management enable at each control moment within a time period can be obtained, thereby improving the control accuracy of the thermal management system and effectively reducing energy consumption.

[0115] Specifically, in one embodiment,

[0116] The control energy consumption cost function refers to the product value of the cumulative sum of the state control sequence corresponding to each control moment in the time period reaching the last moment of the state prediction and the first weight;

[0117] In one embodiment, the cost function of controlling energy consumption is expressed as follows:

[0118] In one embodiment, by constructing a cost function for controlling energy consumption terms, the energy consumption of the actuators of the thermal management system can be incorporated into the optimization target of the thermal management system, thereby enabling the thermal management system to operate more efficiently and sustainably.

[0119] The cost function of the battery temperature control accuracy term refers to the product value of the first difference between the battery real-time temperature at the last moment and the battery target temperature and the second weight;

[0120] In one embodiment, the battery temperature control accuracy cost function is expressed as w2*|T batt (k+t)-T batt,target |.

[0121] In one embodiment, a smaller first difference indicates that the thermal management system is able to more accurately maintain the battery temperature near the battery target temperature.

[0122] The cost function of the inlet temperature control accuracy term refers to the product value of the second difference between the inlet real-time temperature and the inlet target temperature at the last moment and the third weight;

[0123] In one embodiment, the cost function of the inlet temperature control accuracy term is expressed as w3*|T inwtr (k+t)-T inwtr,target |.

[0124] The time control accuracy cost function refers to the product of the third difference between the last moment and the target moment and the fourth weight;

[0125] In one embodiment, the time control accuracy cost function is expressed as w4*|tt target |.

[0126] Among them, t target Indicates the target time when the battery reaches the target battery temperature.

[0127] The cost function refers to the sum of the cost function of the control energy consumption item, the cost function of the battery temperature control accuracy item, the cost function of the inlet temperature control accuracy item and the cost function of the time control accuracy item.

[0128] In one embodiment, the cost function constructed by the present disclosure is expressed as follows:

[0129]

[0130] The cost function constructed by the present invention includes a control energy consumption item cost function including the sum of the control energy consumption cost at each control moment, and a battery temperature control accuracy item cost function, an inlet temperature control accuracy item cost function and a time control accuracy item cost function including the difference between the last moment and the target moment. Thus, by utilizing the cost function constructed by the present invention, it is possible to obtain more accurate inlet target temperatures at each control moment within a time period and thermal management enablement at each control moment within a time period, thereby improving the control accuracy of the thermal management system and effectively reducing energy consumption.

[0131] In one embodiment, the constraints are:

[0132] The thermal management enable is a first preset value or a second preset value;

[0133] In one embodiment, the first preset value indicates that the thermal management enable is not enabled, and the second preset value indicates that the thermal management enable is enabled;

[0134] In one embodiment, the first preset value may be 0, and the second preset value may be 1.

[0135] The inlet target temperature is between a first preset temperature and a second preset temperature;

[0136] In one embodiment, the first preset temperature is lower than the second preset temperature.

[0137] In one embodiment, the first preset temperature may be 0, and the second preset temperature may be 30.

[0138] In one embodiment, the constraint condition can be expressed by the following mathematical expression:

[0139]

[0140] In one embodiment, the real-time battery temperature, the target battery temperature, the real-time inlet temperature, the real-time outlet temperature, and the real-time coolant flow rate are obtained from the thermal management system; the real-time vehicle speed and the real-time ambient temperature are obtained from the vehicle controller, and the real-time battery current is obtained from the battery management unit.

[0141] In one embodiment, the thermal management enable is in the on or off state as the thermal management enable constraint condition, and the inlet target temperature is between 0 and 30 as the temperature constraint condition, so as to solve a state control sequence that conforms to the operation rules of the thermal management system; for example, the thermal management enable can only be turned on or off.

[0142] In order to implement the battery thermal management method provided by the embodiment of the present disclosure, the embodiment of the present disclosure also provides a battery thermal management device, such as Figure 2 As shown. The battery thermal management device 200 includes:

[0143] An acquisition unit 201 is configured to acquire battery operating data related to a temperature change rate of the battery and target data of a thermal management system; wherein the battery operating data includes the real-time battery temperature, and the target data includes the battery target temperature; the battery target temperature is the temperature that the battery needs to reach at a target time;

[0144] Prediction unit 202 is configured to predict the state of the thermal management system based on the battery operating data and the target data, and obtain a state control sequence within a time period to reach the target time; the state control sequence includes an inlet target temperature at each control time within the time period; the inlet target temperature is the temperature of the coolant at the inlet of the coolant circulation pipe at the target time. The coolant circulation pipe is a circulation pipe for the coolant in the thermal management system that exchanges heat with the battery;

[0145] The control unit 203 is used to control the temperature of the coolant at the inlet of the coolant circulation pipeline at each control moment based on the state control sequence, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized.

[0146] In one embodiment, the state control sequence further includes enabling thermal management at each control moment within the time period;

[0147] In one embodiment, the prediction unit 202 is specifically configured to:

[0148] The battery operating data is used as the state parameter, and the inlet target temperature and thermal management enable are used as control parameters. Based on the state parameters and control parameters, the optimization goal is to achieve the optimal control capability of the thermal management system in terms of energy consumption, temperature and time. The inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period are solved.

[0149] In one embodiment, the prediction unit 202 is specifically configured to:

[0150] Substitute state parameters and control parameters into the pre-built state space model;

[0151] Within the preset constraints, with the goal of minimizing the preset cost function, the state-space model is solved to obtain the inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period; among which, the cost function refers to the objective function used to optimize the control capability of the thermal management system in terms of energy consumption, temperature and time.

[0152] In one embodiment, the cost function for controlling the energy consumption item is constructed based on the state control sequence corresponding to each control moment in a time period up to the last moment of the state prediction;

[0153] The cost function of the battery temperature control accuracy term is constructed based on the battery real-time temperature and the battery target temperature at the last moment;

[0154] The cost function of the inlet temperature control accuracy term is constructed based on the inlet real-time temperature and the inlet target temperature at the last moment;

[0155] The time control accuracy cost function is constructed based on the last moment and the target moment.

[0156] The control energy consumption cost function refers to the product value of the cumulative sum of the state control sequence corresponding to each control moment in the time period reaching the last moment of the state prediction and the first weight;

[0157] The cost function of the battery temperature control accuracy term refers to the product value of the first difference between the battery real-time temperature at the last moment and the battery target temperature and the second weight;

[0158] The cost function of the inlet temperature control accuracy term refers to the product value of the second difference between the inlet real-time temperature and the inlet target temperature at the last moment and the third weight;

[0159] The time control accuracy cost function refers to the product of the third difference between the last moment and the target moment and the fourth weight;

[0160] The cost function refers to the sum of the cost function of the control energy consumption item, the cost function of the battery temperature control accuracy item, the cost function of the inlet temperature control accuracy item and the cost function of the time control accuracy item.

[0161] In one embodiment, the thermal management enable is a first preset value or a second preset value; wherein the first preset value indicates that the thermal management enable is not enabled, and the second preset value indicates that the thermal management enable is enabled;

[0162] The inlet target temperature is between a first preset temperature and a second preset temperature; wherein the first preset temperature is lower than the second preset temperature.

[0163] In one embodiment, the acquiring unit 201 is specifically configured to:

[0164] The battery real-time temperature, battery target temperature, inlet real-time temperature, outlet real-time temperature and coolant real-time flow rate are obtained from the thermal management system, and the vehicle real-time speed and ambient real-time temperature are obtained from the vehicle controller, and the battery real-time current is obtained from the battery management unit.

[0165] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principles are the same, which is not limited in this embodiment.

[0166] According to an embodiment of the present disclosure, the present disclosure further provides an electronic device and a non-transitory computer-readable storage medium storing computer instructions.

[0167] Specifically, an embodiment of the present disclosure provides an electronic device, including:

[0168] at least one processor; and

[0169] a memory communicatively connected to at least one processor; wherein,

[0170] The memory stores instructions that can be executed by at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the aforementioned battery thermal management method.

[0171] An embodiment of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the steps of the aforementioned battery thermal management method.

[0172] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, in-vehicle devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0173] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 302 or a computer program loaded from a storage unit 308 into a RAM (Random Access Memory) 303. Various programs and data required for the operation of the device 300 can also be stored in the RAM 303. The computing unit 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0174] Multiple components in device 300 are connected to I / O interface 305, including: input unit 304, such as a keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as a magnetic disk, optical disk, etc.; and communication unit 309, such as a network card, modem, wireless communication transceiver, etc. Communication unit 309 allows device 300 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0175] Computing unit 301 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of computing unit 301 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), various specialized AI (Artificial Intelligence) computing chips, various computing units that run machine learning model algorithms, a DSP (Digital Signal Processor), and any suitable processor, controller, microcontroller, etc. Computing unit 301 performs the various methods and processes described above, such as the battery thermal management method. For example, in some embodiments, the battery thermal management method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by computing unit 301, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the aforementioned battery thermal management method in any other appropriate manner (for example, by means of firmware).

[0176] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System on Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0177] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0178] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0179] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0180] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A battery thermal management method, characterized in that: include: Obtaining battery operating data related to the temperature change rate of the battery and target data of the thermal management system; wherein the battery operating data includes the real-time battery temperature, and the target data includes the battery target temperature of the battery; the battery target temperature is the temperature that the battery needs to reach at the target time; performing a state prediction of the thermal management system based on the battery operating data and the target data, and obtaining a state control sequence within a time period for reaching the target moment; the state control sequence includes the inlet target temperature at each control moment within the time period; the inlet target temperature is the temperature of the coolant at the inlet of the coolant circulation pipe at the target moment; the coolant circulation pipe is a circulation pipe for the coolant in the thermal management system that exchanges heat with the battery; Based on the state control sequence, the temperature of the coolant at the inlet of the coolant circulation pipeline is controlled at each of the control moments, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized.

2. The method according to claim 1, characterized in that The battery operation data also includes real-time inlet temperature, real-time outlet temperature, real-time coolant flow rate, real-time vehicle speed, real-time battery current, and real-time ambient temperature; The state control sequence also includes thermal management enablement at each control moment within the time period; The state prediction of the thermal management system based on the battery operation data and the target data to obtain a state control sequence within a time period to reach the target time includes: The battery operating data is used as a state parameter, and the inlet target temperature and the thermal management enable are used as control parameters. Based on the state parameters and the control parameters, the inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period are solved with the optimization goal of optimizing the control capability of the thermal management system in terms of energy consumption, temperature, and time.

3. The method according to claim 2, characterized in that The performing of state prediction of the thermal management system based on the battery operation data and the target temperature data to obtain a state control sequence within a time period for reaching the target time includes: Substituting the state parameters and the control parameters into a pre-built state space model; Within preset constraints, with the goal of minimizing a preset cost function, the state space model is solved to obtain the inlet target temperature at each control moment in the time period and the thermal management enable at each control moment in the time period; wherein the cost function refers to an objective function used to optimize the control capability of the thermal management system in terms of energy consumption, temperature and time.

4. The method according to claim 3, characterized in that The cost function includes a control energy consumption cost function, a battery temperature control accuracy cost function, an inlet temperature control accuracy cost function and a time control accuracy cost function; The control energy consumption cost function is constructed based on the state control sequence corresponding to each control moment within the time period up to the last moment of state prediction; The battery temperature control accuracy cost function is constructed based on the battery real-time temperature and the battery target temperature at the last moment; The inlet temperature control accuracy cost function is constructed based on the inlet real-time temperature and the inlet target temperature at the last moment; The time control accuracy term cost function is constructed based on the last moment and the target moment.

5. The method according to claim 4, characterized in that The control energy consumption cost function refers to the product value of the cumulative sum of the state control sequence corresponding to each control moment in the time period reaching the last moment of the state prediction and the first weight; The battery temperature control accuracy cost function refers to the product value of the first difference between the battery real-time temperature at the last moment and the battery target temperature and the second weight; The inlet temperature control accuracy cost function refers to the product value of the second difference between the inlet real-time temperature and the inlet target temperature at the last moment and the third weight; The time control accuracy cost function refers to the product value of the third difference between the last moment and the target moment and the fourth weight; The cost function refers to the sum of the control energy consumption cost function, the battery temperature control accuracy cost function, the inlet temperature control accuracy cost function, and the time control accuracy cost function.

6. The method according to claim 3, characterized in that The constraints are: The thermal management enable is a first preset value or a second preset value; wherein the first preset value indicates that the thermal management enable is not turned on, and the second preset value indicates that the thermal management enable is turned on; The inlet target temperature is between a first preset temperature and a second preset temperature; wherein the first preset temperature is lower than the second preset temperature.

7. The method according to claim 2, characterized in that The obtaining of battery operation data related to the temperature change rate of the battery includes: The battery real-time temperature, battery target temperature, inlet real-time temperature, outlet real-time temperature and coolant real-time flow rate are obtained from the thermal management system, and the vehicle real-time speed and ambient real-time temperature are obtained from the vehicle controller, and the battery real-time current is obtained from the battery management unit.

8. A battery thermal management device, characterized in that: include: an acquisition unit, configured to acquire battery operating data related to a temperature change rate of the battery and target data of a thermal management system; wherein the battery operating data includes a real-time battery temperature, and the target data includes a target battery temperature of the battery; the target battery temperature is a temperature that the battery needs to reach at a target time; a prediction unit configured to predict a state of the thermal management system based on the battery operating data and the target data, and obtain a state control sequence within a time period for reaching the target moment; the state control sequence including the inlet target temperature at each control moment within the time period; the inlet target temperature being the temperature of the coolant at the inlet of the coolant circulation pipe at the target moment; the coolant circulation pipe being a circulation pipe for the coolant in the thermal management system that performs heat exchange with the battery; A control unit is used to control the temperature of the coolant at the inlet of the coolant circulation pipeline at each of the control moments based on the state control sequence, so that the control capability of the thermal management system in terms of energy consumption, temperature and time is optimized.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

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