A method and apparatus for heat preservation and charging of battery packs that takes into account electricity prices

Abstract

This application provides a battery pack thermal insulation charging method and apparatus that takes into account electricity prices. The method includes: firstly, acquiring a battery cooling MAP, recording charging and vehicle usage time, and setting target cell temperatures. By setting different cell temperature thresholds for passive thermal insulation and active heating stages, and combining battery cooling characteristics and target heating power, the duration of each stage is determined. Subsequently, based on factors such as parking charging time and vehicle usage time, the charging start time is calculated, and the charging current is determined using a dynamic programming algorithm. By calculating the cost function at different target temperatures, the optimal thermal insulation and heating temperature targets are selected to achieve a charging strategy that maximizes cost-effectiveness. This application achieves a thermal insulation charging process that balances temperature uniformity and lowest cost, reducing charging costs while avoiding the impact of excessively low battery temperature or poor temperature uniformity on charging performance.

Description

Technical Field

[0001] This application relates to the field of charging technology, and in particular to a battery pack heat preservation charging method and apparatus that takes into account electricity prices. Background Technology

[0002] When charging a power battery in a low-temperature environment, its charge transfer speed slows down, leading to decreased charging efficiency and potentially damaging battery performance. To address this issue, thermal insulation charging technology for power batteries is widely used. This technology maintains the battery within a suitable temperature range during charging, improving charging efficiency and protecting battery performance. Thermal insulation charging technology typically employs heating elements or insulation materials, combined with an intelligent control system that monitors battery temperature in real time and adjusts heating power to ensure stable battery operation within a safe range. This technology not only improves the charging efficiency of power batteries in low-temperature environments but also extends battery life, ensuring the reliability and performance of electric vehicles and other electric devices. However, during charging, the temperature uniformity of the power battery is affected by the inhomogeneity of the battery cell structure and material properties, as well as the inconsistent heat transfer caused by the differences in the cell's location within the battery pack. Excessive temperature gradients within the battery pack can severely impact battery performance, leading to incomplete discharge and shortening battery life.

[0003] Meanwhile, in many regions, electricity prices may vary depending on the time of day. This pricing strategy is often called time-of-use pricing or peak-valley pricing. Generally, electricity prices are divided into peak periods, off-peak periods, and flat periods. Peak periods typically occur during the daytime when electricity demand is highest; off-peak periods typically occur at night or in the early morning when demand is lower; and flat periods are the time periods in between. Most current technologies reduce charging costs by allowing users to schedule charging in advance during periods of lower electricity prices to obtain more favorable charging rates.

[0004] As mentioned above, there is currently a lack of a logically clear charging control method that can take into account battery temperature, temperature uniformity, and electricity price. Summary of the Invention

[0005] In view of this, the present application provides a battery pack heat preservation charging method and apparatus that takes into account electricity price, which can achieve a heat preservation charging process with both temperature uniformity and minimum cost, reducing charging costs while avoiding the impact of low battery temperature or poor temperature uniformity on charging performance.

[0006] The technical solution of this application embodiment is implemented as follows:

[0007] In a first aspect, embodiments of this application provide a battery pack heat preservation and charging method that takes into account electricity prices, the method comprising:

[0008] Obtain a battery cooling MAP under low-temperature cold immersion conditions, wherein the battery cooling MAP includes the cooling curve of the center cell and the cooling curve of the edge cell;

[0009] It also records parking and charging time and obtains the user's scheduled vehicle usage time, as well as sets the target temperature of the battery cells when charging is complete;

[0010] The system sets different passive insulation phase end temperatures for the first center cell and the first edge cell, as well as different active heating phase end temperatures for the second center cell and the second edge cell. It also determines the insulation duration of the passive insulation phase based on the battery cooling MAP and the heating duration of the active heating phase based on the target heating power. The passive insulation phase represents the natural cooling process of the vehicle after parking at the ambient temperature, while the active heating phase represents the process of activating the onboard heater to heat the battery pack at the target heating power after the passive insulation phase.

[0011] The duration of the initial charging phase is determined based on the parking charging time, the user's scheduled vehicle usage time, the heat preservation duration, and the heating duration. The battery temperature at the start of charging is determined by the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase. The charging current is determined based on a dynamic programming algorithm.

[0012] Based on the target temperatures of the battery edge cells at the end of different passive heat preservation stages and the target temperatures of the battery edge cells at the end of different active heating stages, the cost function at different target temperatures is calculated according to the charging current sequence determined by the dynamic programming algorithm.

[0013] The target temperature of the battery edge cell at the end of the passive heat preservation stage with the lowest cost function value and the target temperature of the battery edge cell at the end of the active heating stage are selected as the target temperature of this charging strategy, and the current obtained at this target temperature by dynamic programming is used as the charging current sequence.

[0014] Secondly, embodiments of this application also provide a battery pack heat preservation and charging device that takes into account electricity prices, the device comprising:

[0015] The acquisition module is used to acquire a battery cooling MAP under low temperature cold immersion conditions, wherein the battery cooling MAP includes the cooling curve of the center cell and the cooling curve of the edge cell;

[0016] The recording module is used to record parking and charging time, obtain the user's scheduled vehicle usage time, and set the target temperature of the battery cells when charging is complete.

[0017] The setting module is used to set the first center cell temperature and the first edge cell temperature at the end of different passive heat preservation stages, as well as the second center cell temperature and the second edge cell temperature at the end of the active heating stage. It also determines the heat preservation duration of the passive heat preservation stage based on the battery cooling MAP and the heating duration of the active heating stage based on the target heating power. The passive heat preservation stage represents the process of natural cooling of the vehicle at the ambient temperature after parking, while the active heating stage represents the process of activating the onboard heater to heat the battery pack at the target heating power after the passive heat preservation stage.

[0018] The first determining module is used to determine the duration of the start charging phase based on the parking charging time, the user's scheduled vehicle use time, the heat preservation duration, and the heating duration, and to use the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase as the battery temperature at the start of charging, and to determine the charging current based on a dynamic programming algorithm.

[0019] The second determining module is used to calculate the cost function at different target temperatures based on the target temperatures of the battery edge cells at the end of different passive heat preservation stages and the target temperatures of the battery edge cells at the end of different active heating stages, according to the charging current sequence determined by the dynamic programming algorithm.

[0020] The selection module is used to select the target temperature of the battery edge cell at the end of the passive heat preservation stage and the target temperature of the battery edge cell at the end of the active heating stage, which have the lowest cost function value, as the target temperature of this charging strategy, and use the current obtained by dynamic programming at this target temperature as the charging current sequence.

[0021] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the battery pack heat preservation and charging method taking into account electricity price as described in any of the first aspects.

[0022] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, performs the battery pack heat preservation and charging method taking into account electricity prices as described in any one of the first aspects.

[0023] The embodiments of this application have the following beneficial effects:

[0024] (1) The embodiments of this application plan the charging current and time requirements through the idea of ​​dynamic programming algorithm, and at the same time, with the heat preservation strategy, to achieve a heat preservation charging process that can take into account the temperature uniformity and the lowest cost.

[0025] (2) The embodiments of this application realize the battery low-temperature charging preheating function to ensure that the vehicle SOC and battery temperature meet the set requirements when the vehicle is driven.

[0026] (3) The embodiments of this application plan the battery charging status and battery temperature throughout the entire process from parking to driving, so as to avoid the battery temperature being too low and the charging efficiency being low, and can effectively improve the battery life. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart illustrating steps S101-S106 provided in the embodiments of this application;

[0029] Figure 2 This is a MAP diagram of the temperature drop of the edge cells and the center cells provided in the embodiments of this application;

[0030] Figure 3 This is a charging process current, SOC, and cell temperature history diagram provided in an embodiment of this application;

[0031] Figure 4 This is a schematic diagram of the battery pack heat preservation and charging device that takes into account electricity price, provided in an embodiment of this application;

[0032] Figure 5 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0034] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0035] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0036] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0037] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application and is not intended to limit this application.

[0039] See Figure 1 , Figure 1This is a flowchart illustrating steps S101-S106 of the battery pack heat preservation and charging method taking into account electricity prices provided in the embodiments of this application. Figure 1 Steps S101-S106 shown will be explained.

[0040] In step S101, a battery cooling MAP is obtained under low-temperature cold immersion conditions, wherein the battery cooling MAP includes the cooling curve of the center cell and the cooling curve of the edge cell;

[0041] In step S102, the parking charging time is recorded and the user's scheduled vehicle usage time is obtained, and the target temperature of the battery cell when charging is completed is set.

[0042] In step S103, different passive heat preservation phases are set, including the first center cell temperature and the first edge cell temperature at the end of the passive heat preservation phase, as well as the second center cell temperature and the second edge cell temperature at the end of the active heating phase. The heat preservation duration of the passive heat preservation phase is determined based on the battery cooling MAP, and the heating duration of the active heating phase is determined based on the target heating power. The passive heat preservation phase represents the process of natural cooling of the vehicle at the ambient temperature after parking, and the active heating phase represents the process of turning on the on-board heater to heat the battery pack at the target heating power after the passive heat preservation phase.

[0043] In step S104, the duration of the start-of-charge phase is determined based on the parking charging time, the user's scheduled vehicle time, the heat preservation duration, and the heating duration. The battery temperature at the start of charging is the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase. The charging current is determined based on a dynamic programming algorithm.

[0044] In step S105, based on the target temperature of the battery edge cell at the end of different passive heat preservation stages and the target temperature of the battery edge cell at the end of different active heating stages, the cost function at different target temperatures is calculated according to the charging current sequence determined by the dynamic programming algorithm.

[0045] In step S106, the target temperature of the battery edge cell at the end of the passive heat preservation stage with the lowest cost function value and the target temperature of the battery edge cell at the end of the active heating stage are selected as the target temperature of this charging strategy, and the current obtained at this target temperature by dynamic programming is used as the charging current sequence.

[0046] Combining steps S101-S106, this application mainly establishes a cost function J based on electricity price and temperature difference ΔT, plans the charging current and time requirements through dynamic programming algorithm, and combines it with a heat preservation strategy to achieve a heat preservation charging process that balances temperature uniformity and has the lowest cost.

[0047] Specifically:

[0048] (1) Obtaining the battery temperature drop MAP under low-temperature immersion conditions: The vehicle carrying the power battery pack was placed in an environmental chamber. To simulate low-temperature conditions, the temperature range of the environmental chamber was set to -30℃ to 0℃, with a temperature change interval of 2℃. The vehicle was naturally immersed in the cold chamber for 12 hours. Since there was no data communication on the vehicle's CAN network after parking, the test vehicle needed to be powered on for 1 minute every 0.5 hours. Based on simulation experience, the highest and lowest temperatures of the battery cells are generally located in the center cells and the edge cells, respectively. Therefore, to describe the uniformity of the battery pack temperature distribution in detail, the temperature of the battery cells was read and recorded by the data acquisition equipment during the test. The ambient temperature was continuously updated, and finally, the battery cell temperature drop MAP under low-temperature immersion conditions was plotted. Polynomial fitting was performed to determine the relationship between battery cell temperature, time, and ambient temperature.

[0049] After parking, the vehicle is placed in a low-temperature environment, and the battery is naturally cooled under these conditions. The MAP (Modular Temperature Drop Map) of the battery cells under different ambient temperatures, measured from the whole vehicle low-temperature cooling test, or the formula obtained by fitting the temperature drop data of the center and edge cells, can provide a basis for subsequent battery insulation and charging calculations. The MAP diagrams for the temperature drop of the edge and center cells are shown below. Figure 2 As shown.

[0050] (2) Record the parking charging time t_stop and obtain the user's scheduled vehicle usage time t_set, and set the target cell temperature at the end of charging as T_target. In this method, it is necessary to combine the heat preservation strategy and the planned charging current to ultimately achieve the charging goal of the vehicle being fully charged, the battery pack temperature being suitable and having good temperature uniformity, and the electricity cost being low at the user's scheduled vehicle usage time t_set. Therefore, these three parameters have an important impact on the subsequent charging process.

[0051] (3) A combined active and passive battery insulation strategy based on the battery temperature drop curve, comprising two stages: passive insulation and active heating. The passive insulation stage is the natural cooling process under ambient temperature after the vehicle is parked. The temperatures of the center cell and edge cell at the end of the passive insulation stage are set to T_b1 and T_c1, respectively. The duration t_pas of the passive insulation stage can be obtained based on the start and end temperatures of the battery during the passive insulation stage and the battery temperature drop MAP. The active heating stage involves activating the onboard heater after the passive insulation stage to heat the battery pack at a constant power P_heat. The temperatures of the center cell and edge cell at the end of the active heating stage are set to T_b2 and T_c2, respectively. The duration t_heat of the heating stage can be obtained based on the start and end temperatures of the active heating stage and the constant heating power P_heat.

[0052] (4) After determining the durations of the passive insulation and active heating stages, the duration of the initial charging stage, t_charge, can be determined by subtracting t_pas and t_heat from the reserved vehicle time t_set recorded in step (2). The battery temperature at the start of charging is then taken as T_b2 and T_c2, respectively, for the center cell and edge cell at the end of the active heating stage. Subsequently, the charging current is planned using a dynamic programming algorithm. The process is as follows:

[0053] ① Divide the state array. Let the initial SOC of the power battery before charging be S. Since the final SOC is 100%, set the control time step Δt.

[0054] ② Determine the state variables and state transition equations in dynamic programming. When using dynamic programming to solve optimal control problems, it is necessary to discretize the system's state variables x and control variables u, given the initial and final states of the system. The general state-space equations of the system are as follows:

[0055] x t+1 =f(x) t ,u t )

[0056] In the formula, t = 0, 1, 2, ..., t N-1 x t Let be the state variables of the discrete system at stage t. X represents the state space; u t Let be the control variable for the t-th stage of the discrete system. U represents the set of all possible control variables.

[0057] Battery SOC is a key quantity affecting the battery's state of charge. Simultaneously, to ensure temperature uniformity within the battery module and improve charging efficiency, battery temperature distribution is also a crucial consideration during the charging process. Battery temperature is a significant factor influencing battery charging characteristics, with its changes primarily caused by heat generation during charging, heat conduction, and convective heat transfer. Typically, the highest and lowest cell temperatures are located at the center and edge of the battery module, respectively. Therefore, this method only considers the cell temperatures at the edge and center of the battery pack to reflect the temperature distribution within the pack. Thus, in the multi-objective optimization problem of battery charging, battery SOC, edge cell temperatures, and center cell temperatures are selected as the system's state variables.

[0058] (a) SOC calculation

[0059] The relationship between any two stages of SOC is related to the charging rate, and the ultimate requirement of this optimized charging strategy is to obtain a set of optimized current sequences, so the charging current is chosen as the control variable.

[0060] The relationship between battery state variables (SOC) is shown in the following equation.

[0061]

[0062] (b) Calculation of the characterization value of the center cell temperature

[0063] Due to the layout of the central battery cell, its heat convection is not significant. Therefore, the heat generation and heat dissipation are characterized by considering the heat conduction in the thickness direction of the central battery cell, and the temperature of the central battery cell is then approximately calculated.

[0064] According to the battery heat generation rate model (Bernardi model), the heat generation power of the central cell can be expressed as:

[0065]

[0066] In the formula: I is the charging current, R is the ohmic internal resistance of the cell at the current temperature, and T is the charging current. b The current battery temperature. This is the battery temperature entropy coefficient (which can be measured experimentally).

[0067] According to Fourier's law of thermal conductivity, the heat dissipation power of the central battery cell can be expressed as:

[0068]

[0069] In the formula: λ is the thermal conductivity; A is the cell side area; This represents the temperature gradient along the cell thickness direction.

[0070] In heat transfer, Ohm's law (current = potential difference / resistance) from electricity is used to analyze the relationship between heat and temperature difference during heat transfer. Heat flow is likened to current, temperature difference to potential difference, and thermal resistance to resistance. Therefore, the heat transfer power in the battery heat transfer process can be expressed by the following formula:

[0071]

[0072] In the formula: ΔT is the temperature difference between the two objects transferring heat, and R is the thermal resistance of heat transfer.

[0073] The expression for unit thermal resistance is:

[0074]

[0075] In the formula: R i The thermal resistance in the direction of heat flow of the battery cell is K / W; A is the heat flow area, m². 2 L is the thickness of the battery cell in the direction of heat flow, in meters; λ is the thermal conductivity of the battery cell in the direction of heat flow, in W / (m·K).

[0076] Based on the heat transfer path, thermal resistance can also be calculated in parallel and series, just like electrical resistance. The equivalent thermal resistance in parallel and series are expressed as follows:

[0077]

[0078] In the formula: R1 and R2 are the equivalent thermal resistances in parallel and series, respectively: R i is the thermal resistance in the direction of heat flow of the battery cell; m and n are the number of parallel and series batteries.

[0079] Therefore, the heat transfer pattern inside a battery module, taking the central and peripheral cells as examples, can be expressed as follows:

[0080]

[0081] In the formula: ΔT is the temperature difference between the center cell and the edge cell.

[0082] According to the principle of conservation of energy, the energy balance equation inside a battery can be expressed as:

[0083]

[0084] Where: m bat For cell quality, C bat For the specific heat capacity of the battery cell, denoted as the rate of change of temperature.

[0085] The following equations can be combined:

[0086]

[0087] Since dynamic programming is a backward calculation process, the characteristic value of the central cell temperature at time t is:

[0088]

[0089] (c) Calculation of the characterization value of the edge cell temperature

[0090] Compared to the center cell, the edge cells exhibit more significant heat dissipation through convection with the air, in addition to inter-cell heat conduction. Therefore, it is necessary to consider cell heat generation, inter-cell heat conduction, and cell-air convection heat transfer simultaneously to approximate the temperature of the edge cells. Thus, the energy balance equation within the edge cell is:

[0091]

[0092] In the formula: q c q represents the heat generation power of the battery cell. d q represents the convective heat transfer power of the edge cell. t This refers to the heat conduction power between battery cells.

[0093] From the battery heat generation rate model (Bernardi model):

[0094]

[0095] According to Newton's law of cooling, the convective heat transfer power can be expressed as:

[0096] q d =hS(T c -T a )

[0097] Where: h is the convective heat transfer coefficient, T c T a These represent the edge cell temperature and the air temperature inside the battery pack, which are approximately the ambient temperature, respectively, and S is the convective heat transfer area.

[0098] The thermal conductivity between battery cells is:

[0099]

[0100] Combining the above equations, we have:

[0101]

[0102] Similarly, the temperature of the edge cell at time t is characterized as follows:

[0103]

[0104] Based on the above theory, the central cell temperature T is selected in this method. b Edge cell temperature T c The battery SOC is the state variable, and the charging current I is the control variable. The discrete state transition equations required for dynamic programming are then obtained as follows:

[0105]

[0106] Considering charging safety and the power limitations of charging stations, and in order to control the battery pack temperature within a reasonable range, the following constraints can be added:

[0107]

[0108] ③ Determine the cost function required for dynamic programming. The final planned current trajectory must simultaneously satisfy the minimum cost and temperature uniformity. Therefore, the cost function must include two factors: the electricity price p and the temperature difference ΔT. The cost function can be determined as follows:

[0109] J = αp(t) + (1-α)ΔT(t)

[0110] ΔT=T bt -T ct

[0111] In the formula: α is the weighting coefficient; p(t) is the price function; ΔT(t) is the maximum temperature difference function of the module, which is approximated by the temperature difference between the central cell and the edge cells.

[0112] The cost function for each control period ultimately has the following form:

[0113]

[0114] ④ Reverse solution. Set the target temperature for charging completion as T_target. Use T_target to deduce the cell temperature at the previous moment, and simultaneously calculate the cost function for each time step. Within each control step, continuously update the temperature state of the center and edge cells by using the temperature characterization values ​​until the initial SOC cell temperature state values ​​T_b2 and T_c2 are obtained. These values ​​will be used to guide the heat preservation strategy before charging begins.

[0115] Record the cost function, central cell temperature characterization value, edge cell temperature characterization value, and SOC value at each control time step during the back-calculation process. Select the charging current with the minimum cost function in this control period as the planned current value in this control step, and continue the dynamic programming algorithm until the SOC reaches the initial SOC value.

[0116] ⑤ Charging current trajectory acquisition. The charging current trajectory from the start to the end of charging is determined by selecting the charging current corresponding to the minimum cost function under each control period, and the time requirement of each state transition process is accumulated as the time requirement of the entire charging process.

[0117] During charging, the temperatures of the center and edge cells are approximately the highest and lowest temperatures of the battery, respectively. Due to the charging current, the cell temperature continuously rises during charging, with the center cell temperature consistently higher than the edge cell temperature. However, by optimizing the charging current, the heat transfer rate from the high-temperature cell to the low-temperature cell can be controlled, reducing the temperature difference between cells and improving the uniformity of battery temperature distribution. Simultaneously, charging costs can be reduced, thus lowering the overall charging cost for the vehicle.

[0118] (5) In step (2), set the target temperatures of the battery edge cells at the end of different passive heat preservation stages, T_c11, T_c12, ..., T_c1m, and the target temperatures of the battery edge cells at the end of the active heating stage, T_c21, T_c22, ..., T_c2n, and optimize the corresponding charging current sequence according to step (3), and calculate the cost function at different target temperatures:

[0119]

[0120] In the formula, p heat For heating power consumption costs; pcharge The charging power consumption cost is represented by T_b3 and T_c3, which are the temperatures of the center and edge cells of the battery at the end of charging, respectively, and β is the weighting coefficient.

[0121] The target temperatures T_c1i of the battery edge cells at the end of the passive heat preservation stage (which has the lowest cost function value) and T_c2j of the battery edge cells at the end of the active heating stage are selected as the target temperatures for this charging strategy. The current optimized at these target temperatures using dynamic programming is used as the charging current sequence to ensure the economy of the vehicle charging process and to ensure that the battery temperature at vehicle start-up is close to the target temperature. The charging process current, SOC, and cell temperature history graphs are shown below. Figure 3 As shown.

[0122] In summary, the embodiments of this application have the following beneficial effects:

[0123] (1) The embodiments of this application plan the charging current and time requirements through the idea of ​​dynamic programming algorithm, and at the same time, with the heat preservation strategy, to achieve a heat preservation charging process that can take into account the temperature uniformity and the lowest cost.

[0124] (2) The embodiments of this application realize the battery low-temperature charging preheating function to ensure that the vehicle SOC and battery temperature meet the set requirements when the vehicle is driven.

[0125] (3) The embodiments of this application plan the battery charging status and battery temperature throughout the entire process from parking to driving, so as to avoid the battery temperature being too low and the charging efficiency being low, and can effectively improve the battery life.

[0126] Based on the same inventive concept, this application also provides a battery pack heat preservation and charging device that corresponds to the battery pack heat preservation and charging method that takes into account electricity price in the first embodiment. Since the principle of the device in this application is similar to the battery pack heat preservation and charging method that takes into account electricity price, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0127] like Figure 4 As shown, Figure 4 This is a schematic diagram of the structure of the battery pack heat preservation and charging device 400 that takes into account electricity prices, as provided in an embodiment of this application. The battery pack heat preservation and charging device 400 that takes into account electricity prices includes:

[0128] The acquisition module 401 is used to acquire a battery cooling MAP under low temperature cold immersion conditions, wherein the battery cooling MAP includes the cooling curve of the center cell and the cooling curve of the edge cell.

[0129] The recording module 402 is used to record the parking and charging time, obtain the user's scheduled vehicle usage time, and set the target temperature of the battery cell when charging is complete.

[0130] The setting module 403 is used to set the first center cell temperature and the first edge cell temperature at the end of different passive heat preservation stages, and the second center cell temperature and the second edge cell temperature at the end of the active heating stage. It also determines the heat preservation duration of the passive heat preservation stage based on the battery cooling MAP and the heating duration of the active heating stage based on the target heating power. The passive heat preservation stage represents the process of natural cooling of the vehicle at the ambient temperature after parking, while the active heating stage represents the process of activating the onboard heater to heat the battery pack at the target heating power after the passive heat preservation stage.

[0131] The first determining module 404 is used to determine the duration of the start charging phase based on the parking charging time, the user's scheduled vehicle use time, the heat preservation duration, and the heating duration, and to use the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase as the battery temperature at the start of charging, and to determine the charging current based on a dynamic programming algorithm.

[0132] The second determining module 405 is used to calculate the cost function at different target temperatures based on the target temperatures of the battery edge cells at the end of different passive heat preservation stages and the target temperatures of the battery edge cells at the end of different active heating stages, according to the charging current sequence determined by the dynamic programming algorithm.

[0133] The selection module 406 is used to select the target temperature of the battery edge cell at the end of the passive heat preservation stage with the lowest cost function value and the target temperature of the battery edge cell at the end of the active heating stage as the target temperature of this charging strategy, and use the current obtained by dynamic programming at this target temperature as the charging current sequence.

[0134] Those skilled in the art should understand that Figure 4 The functions of each unit in the battery pack heat preservation and charging device 400 that takes into account electricity price can be understood with reference to the relevant description of the aforementioned battery pack heat preservation and charging method that takes into account electricity price. Figure 4 The functions of each unit in the battery pack heat preservation and charging device 400 that takes electricity price into account can be realized by a program running on a processor or by specific logic circuits.

[0135] In one possible implementation, obtaining the battery temperature drop MAP under low-temperature cold immersion conditions includes:

[0136] The vehicle carrying the power battery pack was placed in an environmental chamber with a temperature range of -30℃ to 0℃ and a temperature change interval of 2℃. The vehicle was naturally immersed in cold water for 12 hours. The vehicle was powered on for 1 minute every 0.5 hours to communicate via the CAN network. The temperature of the battery cells was read and recorded by the data acquisition device, and the ambient temperature was updated. A MAP of the battery cell temperature drop under low-temperature immersion conditions was completed, and polynomial fitting was performed to determine the relationship between battery cell temperature, time, and ambient temperature.

[0137] In one possible implementation, the step of determining the duration of the initial charging phase based on the parking charging time, the user's scheduled vehicle usage time, the heat preservation duration, and the heating duration, and using the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase as the battery temperature at the start of charging, and determining the charging current based on a dynamic programming algorithm, includes:

[0138] Divide the state array; let the initial SOC of the power battery before charging be S, and since the final SOC is 100%, set the control time step Δt;

[0139] Determine the state variables and state transition equations in dynamic programming; the state-space equations of the system are:

[0140] x t+1 =f(x) t ,u t )

[0141] In the formula, t = 0, 1, 2, ..., t N-1 x t Let be the state variables of the discrete system at stage t.

[0142] X represents the state space; u t Let be the control variable for the t-th stage of the discrete system. U represents the set of all feasible control variables;

[0143] The battery SOC, edge cell temperature, and center cell temperature are selected as the state variables of the system, and the charging current I is the control variable. The discrete state transition equation required for dynamic programming is constructed.

[0144] Determine the cost function required for dynamic programming, wherein the cost function includes electricity price factors and temperature difference factors;

[0145] The target temperature for charging completion is set as T_target. The cell temperature at the previous moment is calculated by back-calculating T_target, and the cost function at each time step is calculated. Within each control step, the temperature state of the center and edge cells is continuously updated by back-calculating the temperature characterization value until the cell temperature state values ​​T_b2 and T_c2 at the initial SOC are obtained, which are used to guide the heat preservation strategy before charging begins.

[0146] Record the cost function, central cell temperature characterization value, edge cell temperature characterization value, and SOC value at each control time step during the back-calculation process. Select the charging current with the minimum cost function in that control period as the planned current value in that control step and continue the dynamic programming algorithm until the SOC reaches the initial SOC value.

[0147] The charging current trajectory from the start to the end of charging is determined by selecting the charging current corresponding to the minimum cost function under each control period, and the time requirement of each state transition process is accumulated as the time requirement of the entire charging process.

[0148] Set the target temperatures of the battery edge cells at the end of different passive heat preservation stages to 5℃, 0℃, ..., -20℃, and the target temperatures of the battery edge cells at the end of the active heating stage to 4℃, 6℃, ..., 10℃, and obtain the corresponding charging current sequence according to optimization, and calculate the cost function at different target temperatures;

[0149] The target temperature of the battery edge cell at the end of the passive heat preservation stage with the lowest cost function value, T_c1_opt, and the target temperature of the battery edge cell at the end of the active heating stage, T_c2_opt, are selected as the target temperatures of this charging strategy, and the current optimized by dynamic programming at this target temperature is used as the charging current sequence.

[0150] In one possible implementation, the battery SOC is calculated in the following manner:

[0151]

[0152] Among them, SOC t Let SOC represent the initial SOC value at time t, η represent the charging efficiency, I represent the charging current, C0 represent the nominal capacity of the battery, t0 represent the initial time, and t represent the current time.

[0153] 5. The method according to claim 4, wherein the temperature of the central cell is calculated in the following manner:

[0154] The heat generation and heat dissipation are characterized by considering the heat conduction in the thickness direction of the central battery cell, and the temperature of the central battery cell can be approximately calculated.

[0155] According to the battery heat generation rate model, the heat generation power of the central cell is expressed as:

[0156]

[0157] In the formula: I is the charging current, R is the ohmic internal resistance of the cell at the current temperature, and T is the charging current. b The current battery temperature. This refers to the battery temperature entropy coefficient.

[0158] According to Fourier's law of thermal conductivity, the heat dissipation power of the central battery cell can be expressed as:

[0159]

[0160] In the formula: λ is the thermal conductivity; A is the cell side area; This represents the temperature gradient along the cell thickness direction.

[0161] Ohm's law is used to analyze the relationship between heat and temperature difference in the heat transfer process. Heat flow is likened to electric current, temperature difference to potential difference, and thermal resistance to electrical resistance. The heat transfer power in the battery heat transfer process is also expressed as:

[0162]

[0163] In the formula: ΔT is the temperature difference between the two objects undergoing heat transfer, and R is the thermal resistance of heat transfer;

[0164] The expression for unit thermal resistance is:

[0165]

[0166] In the formula: R i The thermal resistance in the direction of heat flow of the battery cell is K / W; A is the heat flow area, m². 2 L is the thickness of the battery cell in the direction of heat flow, in meters; λ is the thermal conductivity of the battery cell in the direction of heat flow, in W / (m·K).

[0167] Based on the heat transfer path, thermal resistance is calculated using parallel and series resistors. The equivalent thermal resistance for parallel and series resistors are expressed as follows:

[0168]

[0169] In the formula: R1 and R2 are the equivalent thermal resistances in parallel and series, respectively: R i The thermal resistance in the direction of heat flow of the battery cell is m; m and n are the number of parallel and series batteries.

[0170] Therefore, taking the central cell and edge cells as examples, the heat transfer law inside the battery module can be expressed as:

[0171]

[0172] In the formula: ΔT is the temperature difference between the center cell and the edge cells;

[0173] According to the principle of conservation of energy, the energy balance equation inside a battery can be expressed as:

[0174]

[0175] Where: m bat For cell quality, C bat For the specific heat capacity of the battery cell, The rate of change of temperature;

[0176] The following equations can be combined:

[0177]

[0178] Since dynamic programming is a backward calculation process, the characteristic value of the central cell temperature at time t is:

[0179]

[0180] In one possible implementation, the edge cell temperature is calculated as follows:

[0181] To approximate the temperature of the edge cells by considering heat generation within the cells, heat conduction between cells, and cell-air convection heat transfer, the energy balance equation inside the edge cells is as follows:

[0182]

[0183] Where: m bat For the quality of the battery cell, C bat T represents the specific heat capacity of the battery cell. c q represents the temperature of the battery cell. c q represents the heat generation power of the battery cell. d q represents the convective heat transfer power of the edge cell. t This refers to the heat conduction power between battery cells;

[0184] From the battery heat generation rate model, we have:

[0185]

[0186] In the formula: I 2 R′ represents the Joule heat generated by the current I passing through the internal resistance R′ of the battery. This indicates that due to the battery open-circuit voltage U o ′ c With temperature T c Heat generated by the change

[0187] According to Newton's law of cooling, the convective heat transfer power can be expressed as:

[0188] q d =hS(T c -T a )

[0189] Where: h is the convective heat transfer coefficient, T c T a These are the edge cell temperature and the air temperature inside the battery pack, which are approximately the ambient temperature, respectively, and S is the convective heat transfer area.

[0190] The thermal conductivity between battery cells is:

[0191]

[0192] Combining the above equations, we have:

[0193]

[0194] Similarly, the temperature of the edge cell at time t is characterized as follows:

[0195]

[0196] 7. The method according to claim 6, wherein the discrete state transition equation required for the dynamic programming is:

[0197]

[0198] And add at least one of the following constraints:

[0199]

[0200] In one possible implementation, the cost function is:

[0201] J = αp(t) + (1-α)ΔT(t)

[0202] ΔT=T bt -T ct

[0203] In the formula: α is the weighting coefficient; p(t) is the price function; ΔT(t) is the maximum temperature difference function of the module, which is approximated by the temperature difference between the central cell and the edge cells;

[0204] The cost function for each control period ultimately has the following form:

[0205]

[0206] In one possible implementation, the cost function at different target temperatures is calculated in the following manner:

[0207]

[0208] In the formula, p heat For heating power consumption costs; p charge The charging power consumption cost is represented by T_b3 and T_c3, which are the temperatures of the center and edge cells of the battery at the end of charging, respectively, and β is the weighting coefficient.

[0209] The aforementioned battery pack insulation and charging device, which takes electricity prices into account, has the following beneficial effects:

[0210] (1) The embodiments of this application plan the charging current and time requirements through the idea of ​​dynamic programming algorithm, and at the same time, with the heat preservation strategy, to achieve a heat preservation charging process that can take into account the temperature uniformity and the lowest cost.

[0211] (2) The embodiments of this application realize the battery low-temperature charging preheating function to ensure that the vehicle SOC and battery temperature meet the set requirements when the vehicle is driven.

[0212] (3) The embodiments of this application plan the battery charging status and battery temperature throughout the entire process from parking to driving, so as to avoid the battery temperature being too low and the charging efficiency being low, and can effectively improve the battery life.

[0213] like Figure 5 As shown, Figure 5 This is a schematic diagram of the composition structure of the electronic device 500 provided in the embodiments of this application. The electronic device 500 includes:

[0214] The device includes a processor 501, a storage medium 502, and a bus 503. The storage medium 502 stores machine-readable instructions that can be executed by the processor 501. When the electronic device 500 is running, the processor 501 communicates with the storage medium 502 via the bus 503. The processor 501 executes the machine-readable instructions to perform the steps of the battery pack heat preservation and charging method taking into account electricity prices as described in the embodiments of this application.

[0215] In practical applications, the various components in the electronic device 500 are coupled together via a bus 503. It is understood that the bus 503 is used to achieve communication between these components. In addition to a data bus, the bus 503 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 5 The general designated all buses as Bus 503.

[0216] The above-mentioned electronic devices have the following beneficial effects:

[0217] (1) The embodiments of this application plan the charging current and time requirements through the idea of ​​dynamic programming algorithm, and at the same time, with the heat preservation strategy, to achieve a heat preservation charging process that can take into account the temperature uniformity and the lowest cost.

[0218] (2) The embodiments of this application realize the battery low-temperature charging preheating function to ensure that the vehicle SOC and battery temperature meet the set requirements when the vehicle is driven.

[0219] (3) The embodiments of this application plan the battery charging status and battery temperature throughout the entire process from parking to driving, so as to avoid the battery temperature being too low and the charging efficiency being low, and can effectively improve the battery life.

[0220] This application also provides a computer-readable storage medium storing executable instructions. When the executable instructions are executed by at least one processor 501, the battery pack heat preservation and charging method taking into account electricity price described in this application is implemented.

[0221] In some embodiments, the storage medium may be a magnetic random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD ROM), etc.; or it may be a device that includes one or any combination of the above-mentioned memories.

[0222] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0223] As an example, executable instructions may, but do not necessarily, correspond to files in the file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0224] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0225] The aforementioned computer-readable storage media have the following beneficial effects:

[0226] (1) The embodiments of this application plan the charging current and time requirements through the idea of ​​dynamic programming algorithm, and at the same time, with the heat preservation strategy, to achieve a heat preservation charging process that can take into account the temperature uniformity and the lowest cost.

[0227] (2) The embodiments of this application realize the battery low-temperature charging preheating function to ensure that the vehicle SOC and battery temperature meet the set requirements when the vehicle is driven.

[0228] (3) The embodiments of this application plan the battery charging status and battery temperature throughout the entire process from parking to driving, so as to avoid the battery temperature being too low and the charging efficiency being low, and can effectively improve the battery life.

[0229] In the several embodiments provided in this application, it should be understood that the disclosed methods and electronic devices can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0230] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0231] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0232] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a platform server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0233] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for heat preservation and charging a battery pack that takes into account electricity prices, characterized in that, The method includes: Obtain a battery cooling MAP under low-temperature cold immersion conditions, wherein the battery cooling MAP includes the cooling curve of the center cell and the cooling curve of the edge cell; It also records parking and charging time and obtains the user's scheduled vehicle usage time, as well as sets the target temperature of the battery cells when charging is complete; The system sets different passive insulation phase end temperatures for the first center cell and the first edge cell, as well as different active heating phase end temperatures for the second center cell and the second edge cell. It also determines the insulation duration of the passive insulation phase based on the battery cooling MAP and the heating duration of the active heating phase based on the target heating power. The passive insulation phase represents the natural cooling process of the vehicle after parking at the ambient temperature, while the active heating phase represents the process of activating the onboard heater to heat the battery pack at the target heating power after the passive insulation phase. The duration of the initial charging phase is determined based on the parking charging time, the user's scheduled vehicle usage time, the heat preservation duration, and the heating duration. The battery temperature at the start of charging is determined by the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase. The charging current is determined based on a dynamic programming algorithm. Based on the target temperatures of the battery edge cells at the end of different passive heat preservation stages and different target temperatures of the battery edge cells at the end of different active heating stages, the cost function at different target temperatures is calculated according to the charging current sequence determined by the dynamic programming algorithm. The target temperature of the battery edge cell at the end of the passive heat preservation stage with the lowest cost function value and the target temperature of the battery edge cell at the end of the active heating stage are selected as the target temperature of this charging strategy, and the current obtained at this target temperature by dynamic programming is used as the charging current sequence.

2. The method according to claim 1, characterized in that, The acquisition of the battery temperature drop MAP under low-temperature cold immersion conditions includes: The vehicle carrying the power battery pack was placed in an environmental chamber with a temperature range of -30℃ to 0℃ and a temperature change interval of 2℃. The vehicle was naturally immersed in cold water for 12 hours. The vehicle was powered on for 1 minute every 0.5 hours to communicate via the CAN network. The temperature of the battery cells was read and recorded by the data acquisition device, and the ambient temperature was updated. A MAP of the battery cell temperature drop under low-temperature immersion conditions was completed, and polynomial fitting was performed to determine the relationship between battery cell temperature, time, and ambient temperature.

3. The method according to claim 1, characterized in that, The duration of the initial charging phase is determined based on the parking charging time, the user's scheduled vehicle usage time, the heat preservation duration, and the heating duration. The battery temperature at the start of charging is determined using the temperatures of the second center cell and the second edge cell at the end of the active heating phase. The charging current is determined based on a dynamic programming algorithm, including: Divide the state array; let the initial SOC of the power battery before charging be S. Since the final SOC is 100%, set the control time step. ; Determine the state variables and state transition equations in dynamic programming; the state-space equations of the system are: In the formula, t=0,1,2,... , x t For the discrete system t The state variables of each stage , X Representing the state space; u t For the discrete system t Control variables at each stage , U Represents the set of all feasible control variables; Battery SOC, edge cell temperature, and center cell temperature are selected as the system state variables, and charging current is used as the system state variables. To control the variables, we construct the discrete state transition equations required for dynamic programming. Determine the cost function required for dynamic programming, wherein the cost function includes electricity price factors and temperature difference factors; The target temperature for charging completion is set as T_target. The cell temperature at the previous moment is calculated by back-calculating T_target, and the cost function at each control time step is calculated. Within each control time step, the temperature state of the center and edge cells is continuously updated by back-calculating the temperature characterization value until the cell temperature state values ​​T_b2 and T_c2 at the initial SOC are obtained, which are used to guide the heat preservation strategy before charging begins. Record the cost function, central cell temperature characterization value, edge cell temperature characterization value, and SOC value at each control time step during the back-calculation process. Select the charging current with the minimum cost function at that control time step as the planned current value at that control time step, and continue the dynamic programming algorithm until the SOC reaches the initial SOC value. The charging current trajectory from the start to the end of charging is determined by selecting the charging current corresponding to the minimum cost function under each control time step, and the time requirement of each state transition process is accumulated as the time requirement of the entire charging process. Set the target temperatures of the battery edge cells at the end of different passive heat preservation stages as 5℃, 0℃, ..., -20℃, and the target temperatures of the battery edge cells at the end of the active heating stage as 4℃, 6℃, ..., 10℃, and obtain the corresponding charging current sequence according to the optimization, and calculate the cost function at different target temperatures. The target temperatures of the battery edge cells at the end of the passive heat preservation stage and the end of the active heating stage, which have the lowest cost function values, are selected as the target temperatures of this charging strategy. The current optimized by dynamic programming at these target temperatures is used as the charging current sequence.

4. The method according to claim 3, characterized in that, The battery SOC is calculated in the following way: in, This represents the SOC value at time t. Indicates the initial SOC value. η Indicates charging efficiency. I Indicates the charging current. C 0 indicates the battery's nominal capacity. t 0 represents the initial time. t This is the current time.

5. The method according to claim 4, characterized in that, The temperature of the core battery cell is calculated in the following way: The heat generation and heat dissipation are characterized by considering the heat conduction in the thickness direction of the central battery cell, and the temperature of the central battery cell can be approximately calculated. According to the battery heat generation rate model, the heat generation power of the central cell is expressed as: In the formula: I This is the charging current. R The ohmic internal resistance of the battery cell at the current temperature. The current battery temperature. This refers to the battery temperature entropy coefficient. According to Fourier's law of thermal conductivity, the heat dissipation power of the central battery cell can be expressed as: In the formula: Where A is the thermal conductivity; A is the cell side area; This represents the temperature gradient along the cell thickness direction. Ohm's law is used to analyze the relationship between heat and temperature difference in the heat transfer process. Heat flow is likened to electric current, temperature difference to potential difference, and thermal resistance to electrical resistance. The heat transfer power in the battery heat transfer process is also expressed as: In the formula: For heat transfer, the temperature difference between two objects, Thermal resistance for heat transfer; The expression for unit thermal resistance is: In the formula: R i The thermal resistance in the direction of heat flow of the battery cell is K / W; A is the heat flow area, m². 2 L represents the thickness of the battery cell in the direction of heat flow, in meters (m). is the thermal conductivity in the direction of heat flow of the battery cell, W / (m·K); Based on the heat transfer path, thermal resistance is calculated using parallel and series resistors. The equivalent thermal resistance for parallel and series resistors are expressed as follows: In the formula: R1 and R2 are the equivalent thermal resistances in parallel and series, respectively: R i The thermal resistance in the direction of heat flow of the battery cell is m; m and n are the number of parallel and series batteries. Therefore, taking the central cell and edge cells as examples, the heat transfer pattern inside the battery module can be expressed as follows: In the formula: The temperature difference between the center cell and the edge cells; According to the principle of conservation of energy, the energy balance equation inside the battery can be expressed as: In the formula: For cell quality, For the specific heat capacity of the battery cell, The rate of change of temperature; The following equations can be combined: Since dynamic programming is a backward calculation process, the characteristic value of the central cell temperature at time t is: 。 6. The method according to claim 5, characterized in that, Edge cell temperature is calculated as follows: To approximate the temperature of the edge cells by considering heat generation within the cells, heat conduction between cells, and cell-air convection heat transfer, the energy balance equation inside the edge cells is as follows: In the formula: m bat For the quality of the battery cells, C bat This refers to the specific heat capacity of the battery cell. T c The edge cell temperature, For the heat generation power of the battery cell, For edge cell convective heat transfer power, This refers to the heat conduction power between battery cells; From the battery heat generation rate model, we have: In the formula: I 2 R ′ indicates that it is caused by current I Through the internal resistance of the battery R The Joule heat generated This indicates that due to the battery open circuit voltage With temperature T c Heat generated by the change According to Newton's law of cooling, the convective heat transfer power can be expressed as: In the formula: The convective heat transfer coefficient is... , These are the edge cell temperature and the air temperature inside the battery pack, which are approximately the ambient temperature. For convective heat transfer area; The thermal conductivity between battery cells is: Combining the above equations, we have: Similarly, the temperature of the edge cell at time t is characterized as follows: 。 7. The method according to claim 6, characterized in that, The discrete state transition equation required for the dynamic programming is: And add at least one of the following constraints: 。 8. The method according to claim 7, characterized in that, The cost function is: In the formula: These are the weighting coefficients; It is a price function; The maximum temperature difference function of the module is approximated by the temperature difference between the center cell and the edge cells; Finally, the cost function for each control time step has the following form: 。 9. The method according to claim 8, characterized in that, The cost functions at different target temperatures are calculated in the following way: In the formula, For heating power consumption costs; For the cost of charging electricity, and These are the temperatures of the center and edge cells of the battery at the end of charging. These are the weighting coefficients.

10. A battery pack heat preservation and charging device that takes into account electricity prices, characterized in that, The device includes: The acquisition module is used to acquire a battery cooling MAP under low temperature cold immersion conditions, wherein the battery cooling MAP includes the cooling curve of the center cell and the cooling curve of the edge cell; The recording module is used to record parking and charging time, obtain the user's scheduled vehicle usage time, and set the target temperature of the battery cells when charging is complete. The setting module is used to set the first center cell temperature and the first edge cell temperature at the end of different passive heat preservation stages, as well as the second center cell temperature and the second edge cell temperature at the end of the active heating stage. It also determines the heat preservation duration of the passive heat preservation stage based on the battery cooling MAP and the heating duration of the active heating stage based on the target heating power. The passive heat preservation stage represents the process of natural cooling of the vehicle at the ambient temperature after parking, while the active heating stage represents the process of activating the onboard heater to heat the battery pack at the target heating power after the passive heat preservation stage. The first determining module is used to determine the duration of the start charging phase based on the parking charging time, the user's scheduled vehicle use time, the heat preservation duration, and the heating duration, and to use the temperature of the second center cell and the temperature of the second edge cell at the end of the active heating phase as the battery temperature at the start of charging, and to determine the charging current based on a dynamic programming algorithm. The second determining module is used to calculate the cost function at different target temperatures based on the target temperatures of the battery edge cells at the end of different passive heat preservation stages and different target temperatures of the battery edge cells at the end of different active heating stages, according to the charging current sequence determined by the dynamic programming algorithm. The selection module is used to select the target temperature of the battery edge cell at the end of the passive heat preservation stage and the target temperature of the battery edge cell at the end of the active heating stage, which have the lowest cost function value, as the target temperature of this charging strategy, and use the current obtained by dynamic programming at this target temperature as the charging current sequence.

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