Battery control method and device, electronic equipment, medium, product and terminal

Abstract

The application discloses a battery control method and device, electronic equipment, medium, product and terminal, and belongs to the technical field of intelligent terminals. The method comprises the following steps: acquiring terminal state data and / or battery state data; determining a target battery heating control strategy based on the terminal state data and / or the battery state data; and executing the target battery heating control strategy.

Description

Technical Field

[0001] This application belongs to the field of smart terminal technology, specifically relating to a battery control method, device, electronic device, medium, product, and terminal. Background Technology

[0002] Currently, despite the rapid growth of the electric vehicle market, the performance degradation of its power batteries at low temperatures (≤-10℃) remains a serious problem, typically leading to a 30%-50% reduction in the vehicle's driving range. This issue not only harms the user experience but has also become a major technical bottleneck for the widespread adoption of electric vehicles in cold regions.

[0003] Current power batteries exhibit significant energy retention degradation in low-temperature environments, the root causes of which can be attributed to two main mechanisms: 1. Internal resistance polarization heat loss effect: Low temperature leads to an increase in the battery's internal resistance, resulting in severe polarization during discharge. This polarization converts some electrical energy into Joule heat, a small amount of which is used to raise the cell temperature, while the rest is dissipated to the external environment through heat exchange.

[0004] 2. Premature cutoff voltage triggering effect: Increased low-temperature polarization accelerates the reaching of the discharge cutoff voltage, preventing the effective release of residual charge inside the battery and directly reducing the available energy output.

[0005] It is worth noting that the battery polarization voltage is the current multiplied by the internal resistance. The industry's technological evolution is moving towards high-rate, low-internal-resistance cells, but this trend has caused new technical contradictions under low-temperature conditions: low-internal-resistance cells generate significantly less heat at low temperatures. In dynamic conditions such as the China Light-duty vehicle Test Cycle (CLTC), the cell temperature rise rate is slow, and it remains in a high polarization state at the end of the discharge period, triggering the cutoff voltage earlier, resulting in more charge remaining inside the battery and not being released.

[0006] Therefore, the battery loses a significant amount of usable capacity due to excessive low-temperature polarization voltage and reaching the cutoff voltage during fast charging, resulting in a decrease in energy retention rate throughout the entire journey. Summary of the Invention

[0007] The purpose of this application is to provide a battery control method, device, electronic device, medium, product, and terminal that can solve the problem of battery loss of usable capacity due to excessive low-temperature polarization voltage and fast charging reaching the cutoff voltage, resulting in a decrease in energy retention rate throughout the entire journey.

[0008] In a first aspect, embodiments of this application provide a battery control method, including: Acquire terminal status data and / or battery status data; Based on the terminal status data and / or the battery status data, a target battery heating control strategy is determined; The target battery heating control strategy is executed.

[0009] Secondly, embodiments of this application provide a battery control device, including: The acquisition module is used to acquire terminal status data and / or battery status data; The determination module is used to determine the target battery heating control strategy based on the terminal status data and / or the battery status data; An execution module is used to execute the target battery heating control strategy.

[0010] Thirdly, embodiments of this application also provide an electronic device, including a memory, a transceiver, and a processor: The memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs in the memory and execute the method as described in the first aspect above.

[0011] Fourthly, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing a processor to perform the method described in the first aspect above.

[0012] Fifthly, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0013] In this embodiment, terminal status data and / or battery status data are first acquired, and a target battery heating control strategy is determined based on the terminal status data and / or battery status data. The target battery heating control strategy is then executed. That is, the target battery heating control strategy is dynamically adjusted according to different terminal status data and / or battery status data. A portion of the battery energy is used to quickly heat the battery to shorten the time the battery is in a low temperature and high internal resistance state, thereby maximizing the energy gain of the battery. Compared with directly adopting a fixed heating strategy, this can improve the energy retention rate of the battery. Attached Figure Description

[0014] Figure 1 This is a schematic flowchart of the battery control method provided in the embodiments of this application; Figure 2 This is a schematic flowchart of the battery control method provided in the embodiments of this application; Figure 3 This is a schematic diagram of the battery control device provided in the embodiments of this application; Figure 4 This is a structural block diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0016] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0017] Currently, battery cells with higher internal resistance at low temperatures exhibit higher energy retention rates in CLTC testing. The underlying physical reason is that higher internal resistance generates more Joule heat, accelerating battery temperature recovery and shortening the duration of low temperatures. Conversely, lower internal resistance weakens self-heating capabilities, prolonging the high-polarization state and amplifying incomplete energy release defects. This finding reveals the inherent limitations of traditional low-internal-resistance technologies in low-temperature scenarios, highlighting the urgent need to address the energy release bottleneck of low-internal-resistance cells under dynamic operating conditions.

[0018] To address low-temperature performance degradation, approaches have primarily focused on three areas: preheating technology, material and structural optimization, and system-level solutions. However, significant shortcomings remain. External heating element preheating technology increases costs and causes uneven battery temperature distribution. Furthermore, pulse self-heating preheating technology relies on preset parameter settings and lacks real-time dynamic optimization capabilities. Improving cell low-temperature characteristics through material and structural optimization also faces cost and engineering bottlenecks, with limited benefits. System-level solutions for vehicle-to-charger coordinated heating are highly dependent on hardware, have poor user compatibility, and significantly increase costs.

[0019] Therefore, embodiments of this application provide a battery control method, device, electronic device, medium, product, and terminal that can dynamically adjust the target battery heating control strategy based on different terminal state data and / or battery state data. By using a portion of the battery energy to rapidly heat the battery, the time the battery is in a low-temperature, high-internal-resistance state is shortened, thereby maximizing the battery's energy gain. Compared to directly adopting a fixed heating strategy, this can improve the battery's energy retention rate.

[0020] The battery control method provided in this application will be described below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0021] Example 1 like Figure 1 As shown in the figure, this application provides a battery control method that can be applied to a terminal, such as a vehicle or an intelligent robot, which requires battery power.

[0022] The above-mentioned battery control method may specifically include the following steps: Step 101: Obtain terminal status data and / or battery status data.

[0023] Specifically, when the terminal is powered on and the battery heating mode is activated, the terminal status data and / or the terminal's battery status data are first acquired. The terminal status data refers to the terminal status data obtained at the time of acquisition.

[0024] In one embodiment, the terminal status data includes, but is not limited to, at least one of the following: terminal moving speed, driving power, and air conditioning power consumption.

[0025] Example: If the terminal is a vehicle, the terminal status data includes, but is not limited to, at least one of the following: terminal moving speed collected via the Controller Area Network (CAN) bus, real-time drive power output via the Vehicle Control Unit (VCU), and air conditioning power consumption collected via the Heating Ventilation and Air-Conditioning (HVAC) controller.

[0026] In one embodiment, the battery state data includes at least one of the following: battery temperature, battery current, battery voltage, and battery state of health. Specifically, battery temperature refers to the battery temperature (e.g., -10°C) acquired in real time using a negative temperature coefficient thermistor (NTC) or a Pt1000 platinum resistance thermometer (i.e., a platinum resistance temperature sensor with a nominal resistance of 1000 Ω at 0°C). Battery current refers to the battery current acquired in real time using a Hall effect sensor and the predicted current of the battery at various future times. Battery voltage refers to the battery voltage acquired in real time using an Analog Front End (AFE) chip and the predicted voltage of the battery at various future times. Battery state of health refers to the battery state of health (SOH) estimated in real time by the Battery Management System (BMS) and the predicted battery state of health at various future times.

[0027] The following explains the process of obtaining the predicted current, predicted voltage, and predicted battery health status at various future moments: Taking a vehicle as an example, when the vehicle is powered on and the battery heating mode is activated, the driving path information of the vehicle from the first location to the second location is obtained. This driving path information includes, but is not limited to, at least one of the following: the planned driving path from the first location to the second location of the vehicle, the road congestion information in the planned driving path obtained through traffic platform data, the road types passed through the planned driving path (such as: highway, urban area, mountain road, etc.), the coordinates of the second location, and the remaining mileage information of the vehicle obtained through the application programming interface (API) of the navigation map (such as: 200km).

[0028] When the vehicle is powered on and the battery heating mode is activated, the driving environment information of the vehicle from the first location to the second location is obtained. The driving environment information includes, but is not limited to, at least one of the following: ambient temperature predicted through a meteorological service interface, and altitude obtained through a Geographic Information System (GIS).

[0029] Based on the vehicle's driving path information from the first position to the second position and the driving environment information, the predicted current, predicted voltage, and predicted battery health status at various future moments are predicted. The above embodiment employs a multi-source data fusion architecture for data acquisition to predict the predicted current, predicted voltage, and predicted battery health status at various future moments, in order to subsequently determine a suitable target battery heating control strategy.

[0030] Step 102: Determine the target battery heating control strategy based on the terminal status data and / or the battery status data.

[0031] Specifically, based on different terminal status data and / or battery status data, the target battery heating control strategy is dynamically adjusted. A portion of the battery energy is used to rapidly heat the battery, thereby shortening the time the battery is in a low-temperature, high-internal-resistance state and maximizing the battery's energy gain. Compared to directly adopting a fixed heating strategy, this can improve the battery's energy retention rate.

[0032] Step 103: Execute the target battery heating control strategy.

[0033] Specifically, after determining the target battery heating control strategy, the target battery heating control strategy is executed to heat the battery, shorten the time the battery is in a low temperature and high internal resistance state, and maximize the energy gain of the battery.

[0034] In this embodiment, terminal status data and / or battery status data are first acquired, and a target battery heating control strategy is determined based on the terminal status data and / or battery status data. The target battery heating control strategy is then executed. That is, the target battery heating control strategy is dynamically adjusted according to different terminal status data and / or battery status data. A portion of the battery energy is used to quickly heat the battery to shorten the time the battery is in a low temperature and high internal resistance state, thereby maximizing the energy gain of the battery. Compared with directly adopting a fixed heating strategy, this can improve the energy retention rate of the battery.

[0035] Example 2 Step 102, based on the terminal status data and / or the battery status data, determines the target battery heating control strategy, including: Based on the terminal status data and / or the battery status data, predict the first dischargeable energy of the battery and the predicted temperature data of the battery at each future time. Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, a target battery heating control strategy is determined from at least one of the battery heating control strategies.

[0036] Specifically, based on terminal status data and / or battery status data, the system predicts the battery's dischargeable energy at the current moment (denoted as the first dischargeable energy) and the predicted temperature data of the battery at various future moments. The first dischargeable energy is the battery's dischargeable energy before the target battery heating control strategy is implemented. The current moment refers to the moment when the terminal status data and the target battery status data are collected.

[0037] Based on terminal state data and / or battery state data, first dischargeable energy, and predicted battery temperature data at various future times, a target battery heating control strategy that maximizes the energy gain of the battery is determined from at least one battery heating control strategy. That is, the target battery heating control strategy is dynamically adjusted according to different terminal state data and / or battery state data, first dischargeable energy, and predicted battery temperature data at various future times. A portion of the battery energy is used to quickly heat the battery to shorten the time the battery is in a low temperature and high internal resistance state, thereby maximizing the energy gain of the battery.

[0038] Example 3 The step of predicting the first dischargeable energy of the battery and the predicted temperature data of the battery at various future times based on the terminal state data and / or the battery state data specifically includes: Obtain the user's historical usage information and historical charging information for the terminal; Based on the historical usage information and the historical charging information, the user's historical behavior characteristic parameters are determined; Based on at least one of the terminal status data, the battery status data, and the historical behavior characteristic parameters, predict the first dischargeable energy of the battery and the predicted temperature data of the battery at each future time.

[0039] Specifically, taking a vehicle as an example, historical usage information refers to the user's historical driving information (such as acceleration, braking, turning, gear usage, etc.), and historical charging information refers to the user's historical charging information (such as charging duration, interval between two consecutive charges, charging power, etc.). When the vehicle is powered on and the battery heating mode is activated, the user's historical usage information and historical charging information are first acquired. Based on these information, historical behavioral characteristic parameters of the user are generated to accurately reproduce the user's unique driving-charging panoramic profile.

[0040] At least one of the following data—terminal status data, battery status data, and historical behavioral characteristic parameters—is input into the battery status prediction model (i.e., simulation model) to predict the energy retention rate (i.e., the first dischargeable energy) and estimate the predicted temperature data of the battery at various future times. Because the battery status prediction model has undergone multi-condition verification testing at the battery pack level, including but not limited to CLTC cycle conditions, room temperature supercharging, and high-rate discharging, the temperature simulation error of the entire battery pack is within ±2℃, thus improving the accuracy of temperature data estimation.

[0041] The battery state prediction model described above is a thermal simulation model architecture, covering, but not limited to, the following types: Equivalent Circuit Model (ECM): A second-order resistor-capacitor (RC) network is used to characterize the dynamic thermoelectric behavior of the battery. Electrochemical mechanism model: Ion diffusion and electrode reactions are described based on a pseudo two-dimensional (P2D) framework; Cloud-based collaborative model: A simplified model is deployed in the edge computing unit, while a high-precision model is run on the cloud server and parameter updates are sent out periodically.

[0042] The common feature of the models in the above examples is that they have the ability to calculate battery heat generation power and can meet the accuracy requirements of the whole vehicle level through the calibration process.

[0043] The following explains the process of building the battery state prediction model: In one embodiment, the polarization internal resistance mapping table construction process in the above battery state prediction model is as follows: (Beginning of Life (BOL) Basic Calibration) 1. Equipment and conditions: Temperature control chamber: -30 ℃ to 55 ℃, in 5 ℃ increments; Test subject: Brand new battery (SOH≈100%).

[0044] 2. HPPC Matrix Design: 3D mesh: Temperature T: -30 ℃, -25 ℃, ..., 55 ℃; Remaining battery power (State of Charge, SOC): 5%, 10%, ..., 95%; Current ratio I: 0.2 C to 6 C, such as: 0.2 C, 0.5 C, 1 C, 2 C, 3 C, 4 C, 5 C, 6 C.

[0045] 3. Pulse-relaxation process: Dynamic parameters are identified by pulse discharge relaxation curves: ohmic internal resistance (R0), polarization internal resistance (R1 / R2), and polarization capacitance (C1 / C2). 4. Mapping table generation: Output a 5-dimensional vector for the triple {T, SOC, I}: RCmap(T, SOC, I) = [R0, R1, R2, C1, C2]; Store it in the calibration database for later viewing and use.

[0046] In one embodiment, the reversible thermal coefficient of the battery state prediction model is calculated: At different temperature points (-20℃, 0℃, 25℃, 45℃), the battery was allowed to stand until it reached thermal equilibrium (i.e., the standing time was ≥6 hours). Record the open-circuit voltage (OCV) of each SOC node (10% interval); Calculate the reversible thermal coefficient:

[0047] in, Indicates the reversible thermal coefficient; Indicates the open-circuit voltage of the battery; This indicates the battery temperature.

[0048] In one embodiment, a corresponding correction coefficient is determined based on the different aging conditions of the vehicle battery and the state of equilibrium (SOH). The RC parameters (i.e., R0, R1, R2, C1, C2) are corrected using the correction coefficient to improve the accuracy of temperature data estimation.

[0049] In one specific embodiment, the battery temperature is calculated using a constructed battery state prediction model: 1. Calculate the heat generation power of the battery at various future moments based on the battery state prediction model (e.g., the Bernardi model, a zero-dimensional thermal model based on energy conservation used to quickly estimate the average volumetric heat generation rate of lithium-ion batteries). :

[0050] Where: I represents the battery current (A), with positive for discharging and negative for charging; V represents the battery's operating voltage; T represents the battery temperature; This represents the reversible thermal coefficient. At the same state of charge (SOC), different values ​​for T and I correspond to the same reversible thermal coefficient.

[0051] 2. Calculate the battery temperature change based on the heat calculation formula and the heat accumulation formula. The formula for cumulative heat production is:

[0052] in, This indicates the instantaneous heat generation power of the battery during charging and discharging (unit: watts, W). Indicates the accumulation (integration) over time; This represents the total heat production (unit: joules J).

[0053] The formula for calculating heat is as follows:

[0054] in, This represents the total heat generated, which is the heat generated or released during the charging and discharging process of the battery. Specific heat capacity (J / (Kg·K)) represents the amount of heat required to raise or lower the temperature by 1 K (Kelvin) per unit mass of battery. Indicates the mass of the battery (g); This indicates the temperature change of the battery between two adjacent moments; It represents the convective heat transfer coefficient (W / (m·K)), which is the efficiency of heat transfer between the fluid and the battery surface; Indicates the ambient temperature of the battery; Indicates the initial temperature of the battery; The effective heat exchange area (unit: m²) represents the surface area where the battery exchanges heat with the surrounding environment.

[0055] By using the battery's temperature data at the current moment and the temperature changes between every two adjacent moments, the predicted temperature data of the battery at each future moment can be estimated.

[0056] Example 4 The step of determining a target battery heating control strategy from at least one battery heating control strategy based on the terminal state data and / or the battery state data, the first dischargeable energy, and the predicted temperature data of the battery at various future times specifically includes: Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, predict the second dischargeable energy after heating the battery using at least one of the battery heating control strategies. The battery heating control strategy corresponding to the maximum value in the second dischargeable energy is determined as the target battery heating control strategy.

[0057] Specifically, the optimization algorithms and battery heating modes supported by the terminal are obtained. Multiple battery heating control strategies (i.e., when, in what form, and how much energy is sacrificed for additional discharge heating) corresponding to each battery heating mode are generated using the optimization algorithms. The control parameters differ for each battery heating control strategy. Based on terminal state data and / or battery state data, predicted battery temperature data at various future moments, and the first dischargeable energy before battery heating, the energy retention rate (i.e., the second dischargeable energy) after battery heating according to each battery heating control strategy is predicted, thus obtaining the second dischargeable energy corresponding to each battery heating control strategy. The second dischargeable energies corresponding to each battery heating control strategy are compared, and the battery heating control strategy corresponding to the maximum value of the second dischargeable energies is determined as the target battery heating control strategy.

[0058] In one embodiment, the optimization algorithm executable by the terminal includes, but is not limited to, one of the following: dynamic programming, model predictive control (MPC), heuristic search, rule base + table lookup, etc.

[0059] In one embodiment, the battery heating modes supported by the terminal include, but are not limited to, one of the following: high-frequency pulse mode and liquid cooling mode.

[0060] The following explanation uses the high-frequency pulse mode as an example: The internal resistance of a battery consists of ohmic impedance, charge transfer impedance, and diffusion impedance. Ohmic impedance, with a response level in the microsecond range, originates from the instantaneous migration of charge carriers; its physical essence is the electrolyte ionic conductivity and the contact resistance between the current collector and the interface. Charge transfer impedance, in the millisecond range, is generated by the charging and discharging of the electrode-electrolyte double layer, following Butler-Volmer kinetics. Diffusion impedance, in the second range, reflects the relaxation of the bulk lithium-ion concentration gradient. During prolonged high-rate charging, slow diffusion can easily lead to lithium-ion supersaturation on the negative electrode surface, triggering irreversible lithium plating and dendrite formation, significantly reducing battery performance. High-frequency pulses, due to their short duration of action in the same current direction, involve very little charge transfer and diffusion, thus significantly reducing the risk of lithium dendrite formation. Furthermore, because the cell resistance is high at low temperatures, high-frequency pulsed currents can rapidly heat the battery. Therefore, by using a high-frequency pulse mode, the battery can be rapidly heated to reach its optimal operating range while maintaining a certain level of safety, maximizing energy utilization.

[0061] For each battery heating control strategy employing a high-frequency pulse mode, based on terminal state data and / or battery state data, predicted battery temperature data at various future moments, and the first dischargeable energy before battery heating, the optimal pulse rate (i.e., pulse current curve), frequency (i.e., repetition frequency of pulse current), duration (i.e., duration of each pulse), and total heating energy budget limit (i.e., the upper limit of the total energy allowed for heating) are predicted using the aforementioned pulse rate, frequency, duration, and total heating energy budget limit. Then, the energy retention rate of the battery after heating using this battery heating control strategy is calculated using the aforementioned pulse rate, frequency, duration, and total heating energy budget limit.

[0062] Example 5 Before executing the target battery heating control strategy in step 103, the method further includes: Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, the heating energy consumption of heating the battery using the target battery heating control strategy is predicted. Based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption, it is determined whether to execute the target battery heating control strategy.

[0063] Specifically, based on terminal status data and / or battery status data, predicted battery temperature data at various future moments, and the first dischargeable energy before battery heating, the heating energy consumption required to heat the battery according to the target battery heating control strategy is predicted, thereby obtaining the heating energy consumption corresponding to each battery heating control strategy.

[0064] Example: For a target battery heating control strategy using a high-frequency pulse mode, based on terminal state data and / or battery state data, predicted battery temperature data at various future moments, and the first dischargeable energy before battery heating, the target battery heating control strategy predicts the optimal pulse rate (i.e., pulse current curve), frequency (i.e., the repetition frequency of the pulse current), duration (i.e., the duration of each pulse), and total heating energy budget limit (i.e., the upper limit of the total energy allowed for heating). Using the above information such as pulse rate, frequency, duration, and total heating energy budget limit, the heating energy consumption required to heat the battery using the target battery heating control strategy is calculated.

[0065] Based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy, it is determined whether the target battery heating control strategy needs to be executed.

[0066] Example 6 The step of determining whether to execute the target battery heating control strategy based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy includes: Based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy, calculate the net energy gain. If the net energy gain is greater than the net energy gain threshold, the target battery heating control strategy is determined to be executed.

[0067] Specifically, after determining the target battery heating control strategy, based on the first dischargeable energy of the battery before heating, the heating energy consumption required to heat the battery using the target battery heating control strategy, and the predicted second dischargeable energy after heating the battery using the target battery heating control strategy, the net energy gain is calculated. This involves comparing the energy sacrificed with the additional energy released due to rapid temperature rise, reduced internal resistance, and reduced polarization. The net energy gain is then compared with a net energy gain threshold. If the net energy gain is greater than the threshold (e.g., 5%), the target battery heating control strategy needs to be implemented to heat the battery, significantly improving the actual usable energy and driving range of the low-internal-resistance battery in low-temperature environments and improving the user experience. If the net energy gain is less than or equal to the net energy gain threshold, the target battery heating control strategy is not required, meaning only discharge is driven.

[0068] In one embodiment, the net energy gain can be calculated using the following formula:

[0069] in, This indicates the net energy gain; This represents the difference between the second dischargeable energy and the first dischargeable energy, i.e., the additional amount of electricity released due to the battery entering the suitable temperature range faster by implementing the target battery heating control strategy. This refers to the heating energy consumption, which is the energy required for the battery to heat up additionally.

[0070] Example 7 To enhance user perception and trust in the battery control system, and to transform the backend algorithm into a transparent technology that is understandable, monitorable, and operable, the method further includes: Display and / or read aloud at least one of the following six items: The first type: the control status information of the battery.

[0071] Specifically, the control status information includes, but is not limited to: battery heating mode activation information (e.g., battery heating mode not activated, battery heating mode in activation), and battery heating control strategy execution status information (e.g., target battery heating control strategy not executed, target battery heating control strategy in execution, target battery heating control strategy completed, high-frequency pulse mode).

[0072] The second method: collecting the target temperature data of the battery.

[0073] Specifically, the target temperature data refers to the real-time collected battery temperature data, which can be displayed based on real-time charts, such as showing the current battery temperature as -12℃.

[0074] The third type: the predicted temperature data of the battery at various future moments.

[0075] Specifically, the predicted battery temperature when reaching the second position can be displayed based on real-time charts.

[0076] The fourth type: energy information corresponding to the execution of the target battery heating control strategy.

[0077] Specifically, the energy information collected and predicted during the execution of the target battery heating control strategy includes, for example, heating energy consumption, net energy gain, first dischargeable energy, second dischargeable energy, consumed energy, and expected additional energy release.

[0078] The fifth type: heating status information corresponding to the execution of the target battery heating control strategy.

[0079] Specifically, the battery temperature before heating (e.g., the current battery temperature is -12℃), the current battery temperature (e.g., the battery temperature has increased from -12℃ to 8℃), the battery temperature reaching the optimal operating range, the state before heating, the state during heating, and the state after heating.

[0080] The sixth type: Mileage information corresponding to the execution of the target battery heating control strategy.

[0081] Specifically, this includes information such as mileage savings and remaining driving range during the execution of the target battery heating control strategy. For example: This time, you saved 1.8 kWh of range, equivalent to an additional 32 kilometers. Another example: If it is detected that traveling to the second location may result in a loss of approximately 50 kilometers of range, activating the battery heating mode is expected to add an additional 38 kilometers of range.

[0082] In one embodiment, after each trip, a shareable optimization report can be automatically generated. The report may include, but is not limited to, detailed driving information such as trip start information, destination information, battery temperature data, battery heating effect, and the target battery heating control strategy adopted. A dedicated page can also be added to represent detailed driving information such as the cumulative benefits brought by the target battery heating control strategy.

[0083] It should be noted that the above content can be displayed through the interface or read aloud by the voice assistant.

[0084] In one embodiment, taking a vehicle as the terminal and the above content as voice broadcast as an example: Scenario 1 (Before the vehicle departs): "Hello, the current battery temperature is -12℃. It has been detected that traveling to the second location may result in a loss of approximately 50 kilometers of range. It is recommended to enable the battery heating mode, which is expected to add an additional 38 kilometers of range. This process will consume approximately 0.8 kWh of electricity for battery preheating, with an overall benefit of approximately 12%. Would you like to enable it?"

[0085] Scenario 2 (Battery heating up): "The battery temperature has risen from -10℃ to 8℃. The battery is heating up and is expected to be completed in 3 minutes. At that time, the range will be increased by an additional 25 kilometers." Scenario 3 (Battery heating complete): "Battery heating is complete, and the battery temperature has reached the optimal operating range. This saves you 1.8 kWh of range, which is equivalent to an additional 32 kilometers."

[0086] Example 8 The method further includes: The control status information of the battery is displayed on the primary display interface; In response to a selection input on the primary display interface, a secondary display interface is displayed, and at least one of the following is displayed on the secondary display interface: The target temperature data of the battery collected; The predicted temperature data of the battery at each future time; Energy information corresponding to the execution of the target battery heating control strategy; Heating status information corresponding to the execution of the target battery heating control strategy; Mileage information corresponding to the execution of the target battery heating control strategy.

[0087] Specifically, the terminal's real-time status display interface, i.e., the Human-Machine Interface (HMI), integrates a primary display interface and a secondary display interface. The primary display interface is the permanent area of ​​the instrument panel / central control screen, while the secondary display interface is the exclusive page that users can access through the central control screen.

[0088] Example: Display the following content in the primary display interface: Status 1: Gray icon - Battery heating mode not activated (i.e., the collected target temperature data of the battery is >10℃ or the net energy gain is ≤5%). State 2: Yellow flashing - Battery heating mode is in progress (i.e., the optimal target battery heating control strategy is being calculated). State 3: Blue Rhythm - Active Heating in Progress (i.e., the target battery heating control strategy is being executed); Status 4: Green light - Optimization complete (meaning the target battery heating control strategy has been executed and the battery has reached its optimal operating temperature).

[0089] Example: Display the following content in the secondary display interface: The collected target temperature data of the battery can be displayed in real time based on a chart, such as showing that the current battery temperature is -12℃.

[0090] The predicted temperature data of the battery at various future moments can be displayed based on real-time charts showing real-time ambient temperature data and predicting the battery temperature when it reaches the second location.

[0091] Real-time ambient temperature data is displayed based on real-time charts. Execution status information of battery heating control strategy, such as: high-frequency pulse mode, etc.; Energy information corresponding to the execution of the target battery heating control strategy, such as: energy consumed, expected additional energy released, and net energy gain.

[0092] Heating status information during the execution of the target battery heating control strategy, such as battery heating duration and battery temperature rise range.

[0093] Mileage information corresponding to the execution of the target battery heating control strategy, such as the range improvement.

[0094] It should be noted that the above battery control method may include at least one of Embodiments 1 to 8. For example: Embodiment 1 may be implemented as an independent embodiment. Embodiments 1+2 may be implemented as independent embodiments. Embodiments 1+2+3 may be implemented as independent embodiments. Embodiments 1+2+4 and 1+2+3+4 may be implemented as independent embodiments. Embodiments 1+2+5, 1+2+3+5, 1+2+4+5, and 1+2+3+4+5 may be implemented as independent embodiments. Embodiments 1+2+5+6 may be implemented as independent embodiments. Examples 1 and 7 can be implemented as independent embodiments; Examples 1, 2, and 7 can be implemented as independent embodiments; Examples 1, 2, 3, and 7 can be implemented as independent embodiments; Examples 1, 2, 4, and 7 can be implemented as independent embodiments; Examples 1, 2, 3, 4, and 7 can be implemented as independent embodiments; Examples 1, 2, 5, and 7 can be implemented as independent embodiments; Examples 1, 2, 3, 5, and 7 can be implemented as independent embodiments; Examples 1, 2, 4, 5, and 7 can be implemented as independent embodiments; Examples 1, 2, 3, 4, 5, and 7 can be implemented as independent embodiments; Examples 1, 2, 5, and 6 can be implemented as independent embodiments; Examples 1, 2, 3, 5, and 6 can be implemented as independent embodiments; Examples 1, 2, 4, 5, and 6 can be implemented as independent embodiments; Examples 1, 2, 3 ... Examples 1+2+3+8 can be implemented as independent embodiments. Examples 1+2+4+8 can be implemented as independent embodiments. Examples 1+2+5+8 can be implemented as independent embodiments. Examples 1+2+5+6+8 can be implemented as independent embodiments. Examples 1+2+3+5+6+8 can be implemented as independent embodiments. Examples 1+2+4+5+6+8 can be implemented as independent embodiments. Examples 1+2+3+4+5+6+8 can be implemented as independent embodiments.Examples 1+7+8 can be implemented as independent examples, examples 1+2+7+8 can be implemented as independent examples, examples 1+2+3+7+8 can be implemented as independent examples, examples 1+2+4+7+8 can be implemented as independent examples, examples 1+2+3+4+7+8 can be implemented as independent examples, examples 1+2+5+7+8 can be implemented as independent examples, examples 1+2+3+5+7+8 can be implemented as independent examples, examples 1+2+4+5+7+8 can be implemented as independent examples, examples 1+2+5+6+7+8 can be implemented as independent examples, examples 1+2+3+5+6+7+8 can be implemented as independent examples, examples 1+2+4+5+6+7+8 can be implemented as independent examples, examples 1+2+3+4+5+6+7+8 can be implemented as independent examples.

[0095] Examples 1+2+3+4+5+6 are given below as independent embodiments: like Figure 2 As shown, step 201: Construct a battery state prediction model.

[0096] Step 202: Obtain terminal status data, battery status data, and historical behavior characteristic parameters.

[0097] Step 203: Input the terminal status data, battery status data, and historical behavior characteristic parameters into the battery status prediction model to predict the battery's first dischargeable energy and the battery's predicted temperature data at each future moment.

[0098] Step 204: Based on terminal status data, battery status data, first dischargeable energy, and predicted battery temperature data at each future time, predict the second dischargeable energy after heating the battery using at least one of the battery heating control strategies, and determine the battery heating control strategy corresponding to the maximum value of the second dischargeable energy as the target battery heating control strategy.

[0099] Step 205: Based on terminal status data, battery status data, first dischargeable energy, and predicted battery temperature data at various future times, predict the heating energy consumption of heating the battery using the target battery heating control strategy.

[0100] Step 206: Calculate the net energy gain based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption.

[0101] Step 207: Determine whether the net energy gain is greater than the net energy gain threshold. If yes, proceed to step 208; otherwise, proceed to step 209.

[0102] Step 208: If the net energy gain is greater than the net energy gain threshold, execute the target battery heating control strategy.

[0103] Step 209: If the net energy gain is less than or equal to the net energy gain threshold, the target battery heating control strategy is not executed.

[0104] In summary, the embodiments of this application, when used in low-temperature environments and when users have extended driving range requirements (such as highway driving), significantly reduce the usable energy lost due to excessive low-temperature polarization voltage or reaching the cutoff voltage during fast charging by sacrificing a small amount of battery energy to accelerate battery self-heating. This ultimately improves the energy retention rate or driving range throughout the entire journey, and is particularly suitable for batteries with low internal resistance and high-rate fast charging capabilities at present. Furthermore, the target battery heating control strategy can be dynamically adjusted and optimized during terminal driving based on travel requirements and battery status to maximize net energy gain, resulting in higher energy utilization efficiency compared to existing battery heating methods.

[0105] The battery control method provided in this application can be executed by a battery control device. This application uses the execution of the battery control method by a battery control device as an example to illustrate the battery control device provided in this application.

[0106] like Figure 3 As shown in the figure, this application embodiment also provides a battery control device 300, specifically including: The acquisition module 301 is used to acquire terminal status data and / or battery status data; The determining module 302 is used to determine a target battery heating control strategy based on the terminal status data and / or the battery status data; The execution module 303 is used to execute the target battery heating control strategy.

[0107] Optionally, when determining the target battery heating control strategy based on the terminal status data and / or the battery status data, the determining module 302 is specifically used for: Based on the terminal status data and / or the battery status data, predict the first dischargeable energy of the battery and the predicted temperature data of the battery at each future time. Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, a target battery heating control strategy is determined from at least one of the battery heating control strategies.

[0108] Optionally, when the determining module 302 predicts the first dischargeable energy of the battery and the predicted temperature data of the battery at various future times based on the terminal state data and / or the battery state data, it is specifically used for: Obtain the user's historical usage information and historical charging information for the terminal; Based on the historical usage information and the historical charging information, the user's historical behavior characteristic parameters are determined; Based on at least one of the terminal status data, the battery status data, and the historical behavior characteristic parameters, predict the first dischargeable energy of the battery and the predicted temperature data of the battery at each future time.

[0109] Optionally, when determining a target battery heating control strategy from at least one battery heating control strategy based on the terminal state data and / or the battery state data, the first dischargeable energy, and the predicted temperature data of the battery at various future times, the determining module 302 is specifically used for: Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, predict the second dischargeable energy after heating the battery using at least one of the battery heating control strategies. The battery heating control strategy corresponding to the maximum value in the second dischargeable energy is determined as the target battery heating control strategy.

[0110] Optionally, the device further includes: The prediction module is used to predict the heating energy consumption of heating the battery using the target battery heating control strategy, based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time. The determining module 302 is further configured to determine whether to execute the target battery heating control strategy based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption.

[0111] Optionally, when determining whether to execute the target battery heating control strategy based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy, the determining module 302 is specifically used for: Based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy, calculate the net energy gain. If the net energy gain is greater than the net energy gain threshold, the target battery heating control strategy is determined to be executed.

[0112] Optionally, the device further includes: Output module, used to display and / or read aloud at least one of the following: The battery controls the control status information of the battery; The target temperature data of the battery collected; The predicted temperature data of the battery at each future time; Energy information corresponding to the execution of the target battery heating control strategy; Heating status information corresponding to the execution of the target battery heating control strategy; Mileage information corresponding to the execution of the target battery heating control strategy.

[0113] Optionally, the output module is further configured to: The battery control status information is displayed on the primary display interface; In response to a selection input on the primary display interface, a secondary display interface is displayed, and at least one of the following is displayed on the secondary display interface: The target temperature data of the battery collected; The predicted temperature data of the battery at each future time; Energy information corresponding to the execution of the target battery heating control strategy; Heating status information corresponding to the execution of the target battery heating control strategy; Mileage information corresponding to the execution of the target battery heating control strategy.

[0114] It should be noted that the battery control device provided in this application embodiment can implement all the method steps implemented in the above battery control method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0115] It should be noted that the division of units in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, 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. The integrated units described above can be implemented in hardware or as software functional units.

[0116] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-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 all or part 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, server, or network device, etc.) or processor 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, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] like Figure 4 As shown, embodiments of this application also provide an electronic device, including a memory 920, a transceiver 910, and a processor 900: Memory 920 is used to store computer programs; Transceiver 910 is used to send and receive data under the control of the processor; Processor 900 is configured to read a computer program from memory and execute the steps of the battery control method as described in any of the above embodiments.

[0118] Among them, Figure 4 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 900) and memory (memory 920). The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 910 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. The processor 900 is responsible for managing the bus architecture and general processing, and the memory 920 can store data used by the processor 900 during operation.

[0119] The processor 900 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0120] The processor executes the battery control method provided in this application embodiment by calling a computer program stored in memory, according to the obtained executable instructions. The processor and memory can also be physically separated.

[0121] It should be noted that the electronic device provided in this application embodiment can implement all the method steps implemented in the above battery control method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0122] Embodiments of this application also provide a processor-readable storage medium storing a computer program for causing the processor to execute the above-described battery control method.

[0123] This application also provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the battery control method embodiments described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0124] This application also provides a terminal, which includes at least one of the battery control device, electronic device, processor-readable storage medium, and computer program product described in the above embodiments.

[0125] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0126] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) to execute the methods described in the various embodiments of this application.

[0127] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A battery control method, characterized in that, include: Acquire terminal status data and / or battery status data; Based on the terminal status data and / or the battery status data, a target battery heating control strategy is determined; The target battery heating control strategy is executed.

2. The method according to claim 1, characterized in that, The step of determining the target battery heating control strategy based on the terminal status data and / or the battery status data includes: Based on the terminal status data and / or the battery status data, predict the first dischargeable energy of the battery and the predicted temperature data of the battery at each future time. Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, a target battery heating control strategy is determined from at least one of the battery heating control strategies.

3. The method according to claim 2, characterized in that, The prediction of the first dischargeable energy of the battery and the predicted temperature data of the battery at various future times, based on the terminal state data and / or the battery state data, includes: Obtain the user's historical usage information and historical charging information for the terminal; Based on the historical usage information and the historical charging information, the user's historical behavior characteristic parameters are determined; Based on at least one of the terminal status data, the battery status data, and the historical behavior characteristic parameters, predict the first dischargeable energy of the battery and the predicted temperature data of the battery at each future time.

4. The method according to claim 2 or 3, characterized in that, The step of determining a target battery heating control strategy from at least one battery heating control strategy based on the terminal state data and / or the battery state data, the first dischargeable energy, and the predicted temperature data of the battery at various future times includes: Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, predict the second dischargeable energy after heating the battery using at least one of the battery heating control strategies. The battery heating control strategy corresponding to the maximum value in the second dischargeable energy is determined as the target battery heating control strategy.

5. The method according to any one of claims 2 to 4, characterized in that, Before executing the target battery heating control strategy, the method further includes: Based on the terminal status data and / or the battery status data, the first dischargeable energy, and the predicted temperature data of the battery at each future time, the heating energy consumption of heating the battery using the target battery heating control strategy is predicted. Based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption, it is determined whether to execute the target battery heating control strategy.

6. The method according to claim 5, characterized in that, The step of determining whether to execute the target battery heating control strategy based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy includes: Based on the first dischargeable energy, the second dischargeable energy corresponding to the target battery heating control strategy, and the heating energy consumption corresponding to the target battery heating control strategy, calculate the net energy gain. If the net energy gain is greater than the net energy gain threshold, the target battery heating control strategy is determined to be executed.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Display and / or read aloud at least one of the following: The control status information of the battery; The target temperature data of the battery collected; The predicted temperature data of the battery at each future time; Energy information corresponding to the execution of the target battery heating control strategy; Heating status information corresponding to the execution of the target battery heating control strategy; Mileage information corresponding to the execution of the target battery heating control strategy.

8. The method according to any one of claims 1 to 7, further comprising: The control status information of the battery is displayed on the primary display interface; In response to a selection input on the primary display interface, a secondary display interface is displayed, and at least one of the following is displayed on the secondary display interface: The target temperature data of the battery collected; The predicted temperature data of the battery at each future time; Energy information corresponding to the execution of the target battery heating control strategy; Heating status information corresponding to the execution of the target battery heating control strategy; Mileage information corresponding to the execution of the target battery heating control strategy.

9. A battery control device, characterized in that, include: The acquisition module is used to acquire terminal status data and / or battery status data; The determination module is used to determine the target battery heating control strategy based on the terminal status data and / or the battery status data; An execution module is used to execute the target battery heating control strategy.

10. An electronic device, characterized in that, Includes memory, transceiver, and processor: The memory is used to store a computer program; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer program in the memory and execute the steps of the battery control method as described in any one of claims 1-8.

11. A processor-readable storage medium, characterized in that, The processor-readable storage medium stores a computer program for causing the processor to perform the steps of the battery control method as described in any one of claims 1-8.

12. A computer program product, characterized in that, The computer program product is stored in a storage medium, and the computer program product is executed by at least one processor to implement the steps of the battery control method as described in any one of claims 1-8.

13. A terminal, characterized in that, The terminal includes at least one of the battery control device of claim 9, the electronic device of claim 10, the processor-readable storage medium of claim 11, and the computer program product of claim 12.

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