Vehicle control method and vehicle

Abstract

The invention relates to a vehicle control method and a vehicle, and belongs to the technical field of vehicle control, and the method comprises the steps: obtaining an environment temperature, and determining the total peak current, corresponding to the environment temperature, of all loads to be started in a load characteristic database; estimating and determining the internal resistance value of the corresponding storage battery by using the storage battery internal resistance model; combining the total peak current, the internal resistance value and the open-circuit voltage of the storage battery, calculating a minimum voltage point when the to-be-started load is started at the same time, comparing the minimum voltage point with a preset safe voltage threshold value to obtain a comparison result, and determining that the starting strategy of the to-be-started load is peak shifting starting or parallel starting based on the comparison result; the starting time of the to-be-started loads is determined based on the starting strategy, the to-be-started loads are controlled to be started based on the starting time, the voltage collapse risk caused by simultaneous starting of multiple loads can be effectively avoided, and the starting reliability and stability of the vehicle electronic system in the low-temperature scene are improved.

Description

Technical Field

[0001] This application relates to the technical field of vehicle control, and more particularly to a vehicle control method and a vehicle. Background Technology

[0002] With the continuous improvement of automotive intelligence and electrification, the vehicle domain controller, as the core unit integrating and managing high-power loads such as air conditioning, seat heating, and headlights, plays a crucial role in ensuring the functional safety of the entire vehicle by ensuring reliable startup in low-temperature environments. In low-temperature environments, the internal resistance of the battery increases significantly and its output capacity decreases. Simultaneously, the inrush current generated by loads such as positive temperature coefficient heaters during low-temperature startup is much higher than at normal temperatures. The system faces the dual pressures of reduced power supply capacity and a surge in instantaneous power demand, making it highly susceptible to startup abnormalities.

[0003] Currently, in existing methods, the vehicle domain controller mostly adopts independent control or a delayed start strategy based on a fixed timing for starting each load. That is, during the initialization phase, the loads are triggered to power on sequentially or in groups according to a preset order. In between, the pre-set delay parameters are used to avoid the superposition of instantaneous currents. And the system can usually maintain basic operation under normal temperature or stable operating conditions.

[0004] In the aforementioned prior art, the fixed delay strategy lacks the ability to perceive the real-time status of the battery and the dynamic characteristics of the load, and cannot adapt to the drastic changes in internal resistance and inrush current at low temperatures. Its blindness and static nature mean that under harsh conditions, the controller may still be reset due to a sudden drop in voltage, which seriously restricts the first start success rate of the vehicle in cold environments and the reliability of the system. Summary of the Invention

[0005] This application addresses, to at least some extent, one of the technical problems in the related art.

[0006] Therefore, this application aims to provide a vehicle control method and a vehicle, which predicts the peak load current and battery internal resistance based on ambient temperature and calculates the lowest voltage point, and intelligently selects the start-up strategy accordingly. This achieves adaptive intelligent scheduling of the start-up sequence of multiple loads, ensures voltage stability under low temperature conditions, and solves the problems of system voltage collapse, controller reset, and poor vehicle start-up reliability caused by the lack of environmental perception capability in the fixed delay start-up strategy in the prior art.

[0007] To achieve the above objectives, in a first aspect, this application provides a vehicle control method applied to a vehicle body domain controller, the control method comprising: Obtain the ambient temperature, and based on the ambient temperature, determine the total peak current of all loads to be started in the load characteristic database corresponding to the ambient temperature; The internal resistance value of the corresponding battery is estimated and determined using the battery internal resistance model; By combining the total peak current, the internal resistance value, and the open-circuit voltage of the battery, calculate the lowest voltage point when all loads to be started start simultaneously; The lowest voltage point is compared with a preset safe voltage threshold to obtain a comparison result. Based on the comparison result, the startup strategy of the load to be started is determined to be either off-peak startup or parallel startup. The startup time of the load to be started is determined based on the startup strategy, and the startup of each load to be started is controlled based on the startup time.

[0008] In existing technologies, each load is started with a fixed timing delay in low-temperature environments, which fails to take into account the dynamic changes in real-time ambient temperature, battery status and load characteristics, resulting in the system often failing to start due to voltage drops in low-temperature environments.

[0009] This application establishes a dynamic correlation mechanism between load characteristics and temperature through the above-mentioned scheme. It predicts the total peak current and battery internal resistance with ambient temperature as the core parameter, and realizes risk-based adaptive selection of startup strategy through voltage prediction, transforming the traditional static startup logic into an intelligent decision-making process based on real-time state perception.

[0010] Furthermore, this application, through proactive prediction and decision optimization, effectively avoids the risk of voltage collapse caused by the simultaneous startup of multiple loads, compared with existing methods that rely on fixed delays and lack environmental adaptability, and significantly improves the startup reliability and stability of vehicle electronic systems in low-temperature scenarios.

[0011] In some embodiments of this application, the ambient temperature is obtained, and the total peak current of all loads to be started in the load characteristic database corresponding to the ambient temperature is determined based on the ambient temperature, including: Based on the ambient temperature, the load characteristic database preset in the vehicle domain controller is queried to obtain the nominal power and inrush current multiple of each load to be started at the ambient temperature; Based on the nominal power and the inrush current multiple, calculate the inrush current value of each of the loads to be started at the ambient temperature; Based on the inrush current value, calculate the total peak current generated when all loads to be started start simultaneously.

[0012] In the technical solution, by establishing a database of load characteristics related to ambient temperature, the accurate quantification of load inrush current is achieved; The load characteristic database pre-stores the nominal power and inrush current multiple of each load to be started under different ambient temperatures, so that the corresponding values ​​can be directly retrieved based on the ambient temperature. The inrush current value and total peak current calculated based on the nominal power and inrush current multiple provide an accurate data basis for subsequent voltage drop prediction, enabling the entire prediction model to have temperature adaptability, thus more accurately reflecting the true electrical characteristics of the load at low temperatures.

[0013] In some embodiments of this application, the internal resistance value of the corresponding battery is estimated and determined using a battery internal resistance model, including: Obtain the state of charge and health status of the battery; Based on the ambient temperature, the state of charge, and the health status, the internal resistance value of the battery is obtained by querying a preset battery internal resistance mapping table or by calculating using a preset battery internal resistance empirical calculation model.

[0014] In the technical solution, by obtaining the state of charge and health of the battery and combining it with the ambient temperature, the internal resistance value is estimated using a battery internal resistance mapping table or an empirical calculation model of the battery internal resistance, which significantly improves the estimation accuracy of the internal resistance value. By fully considering multiple dynamic factors affecting the battery's output capability, especially the battery's aging level and remaining charge, the calculated internal resistance value is closer to the battery's actual state under the current low-temperature and harsh operating conditions. This lays a key foundation for accurately predicting system voltage drops and avoids misjudgments in the startup strategy due to inaccurate internal resistance estimation.

[0015] In some embodiments of this application, the lowest voltage point when all loads to be started simultaneously is calculated by combining the total peak current, the internal resistance value, and the open-circuit voltage of the battery, including: The voltage drop when all loads to be started start simultaneously is calculated by multiplying the total peak current by the internal resistance value. The lowest voltage point is obtained based on the difference between the voltage drop amplitude and the open-circuit voltage of the battery.

[0016] In the technical solution, by combining the predicted total peak current with the estimated battery internal resistance and calculating the theoretical voltage drop based on Ohm's law, the lowest voltage point can be determined. This transforms abstract current and internal resistance parameters into intuitive voltage risk prediction values, enabling the system to quantitatively assess voltage stability under the worst operating conditions. By comparing the theoretical minimum voltage with the open-circuit voltage, potential voltage collapse risks can be identified in advance, providing a clear and reliable quantitative basis for the dynamic selection of startup strategies, and achieving a key leap from parameter perception to risk prediction.

[0017] In some embodiments of this application, the lowest voltage point is compared with a preset safe voltage threshold to obtain a comparison result. Based on the comparison result, the startup strategy of the load to be started is determined to be either off-peak startup or parallel startup, including: If the lowest voltage point is less than the preset safe voltage threshold, then the startup strategy is off-peak startup; If the lowest voltage point is greater than or equal to the safe voltage threshold, then the startup strategy is parallel startup.

[0018] In the technical solution, the predicted minimum voltage point is directly compared with the safe voltage threshold. When the minimum voltage point is lower than the safe voltage threshold, the peak-shaving startup strategy is automatically triggered to avoid risks; otherwise, an efficient parallel startup strategy is adopted. This makes the selection of startup strategy no longer fixed or blind, but based on the quantitative assessment of the contradiction between the current system power supply capacity and load demand. This achieves adaptive switching of startup mode, which maximizes startup efficiency while ensuring system safety, and balances reliability and timeliness.

[0019] In some embodiments of this application, the startup time of the load to be started is determined based on the startup strategy, and the startup of each load to be started is controlled based on the startup time, including: If the startup strategy is off-peak startup, then each load to be started is sorted based on the preset safety priority and the inrush current value to obtain the load startup order list; Based on the load startup order list, a preset delay time is inserted between the loads to be started with different security priorities; Based on the load startup sequence list and the delay time, the vehicle domain controller sequentially controls the drive circuits of each load to be started to output enable signals, so that each load to be started can be started in staggered shifts.

[0020] In the technical solution, after determining to adopt staggered start-up, a two-dimensional sorting mechanism based on safety priority and inrush current value is introduced to generate a load start-up sequence, ensuring that key functions related to driving safety are started first. By inserting configurable delays between different priority groups, the simultaneous startup of multiple high-current loads in a short period of time is effectively avoided. The loads are driven sequentially according to the generated precise timing sequence, which realizes the dispersion of power peaks on the time axis and ensures a smooth transition of system voltage.

[0021] In some embodiments of this application, if the startup strategy is off-peak startup, then the loads to be started are sorted based on a preset safety priority and the inrush current value to obtain a load startup order list, including: All loads to be started are grouped and sorted according to the security priority order. Within the same safety priority group, the loads are sorted according to the magnitude of their inrush current values ​​to obtain a load start-up order list.

[0022] In the technical solution, by sorting the inrush currents according to their magnitude within the same priority group, a smooth transition management of the inrush current is achieved, ensuring the core requirement of functional safety and enabling high-priority loads to receive power supply first. Under the premise of meeting safety requirements, by arranging the loads within the group in ascending order of inrush current, the current surge introduced by each startup is minimized, which is conducive to the voltage recovery of the power supply network. An optimal balance can be achieved between safety and smoothness, so that the generated startup sequence not only meets functional safety requirements, but also minimizes the instantaneous pressure on the power supply system.

[0023] In some embodiments of this application, based on the load startup sequence list and the delay time, the vehicle domain controller sequentially controls the drive circuits of each load to be started to output enable signals, so that each load to be started starts off in staggered shifts, including: Real-time monitoring of the actual voltage of the power supply network bus; If the actual voltage drop is lower than the safety threshold, the delay time is shortened to the first delay time. If the actual voltage drop exceeds the safety threshold, the delay time will be extended to a second delay time or the startup of the load to be started will be suspended.

[0024] In the technical solution, by introducing a dynamic delay adjustment mechanism based on actual voltage monitoring during the off-peak start-up process, the system no longer mechanically executes the preset delay, but can be optimized in real time according to the actual response of the power supply network. When the voltage drop is detected to be below the safety threshold, the startup process is accelerated and efficiency is improved by shortening the subsequent delay. When the voltage drop is abnormal or the recovery is slow, the startup is provided with stronger protection by extending the delay or pausing the startup process. This enhances the system's adaptability to uncertainties such as different battery states and line impedances, and further improves the robustness and safety of the startup process.

[0025] In some embodiments of this application, if the startup strategy is parallel startup, the vehicle domain controller simultaneously outputs enable signals to the drive circuits of all loads to be started, so that all loads to be started can be started in parallel.

[0026] In the technical solution, by simultaneously outputting enable signals to all load drive circuits after determining parallel startup, the power supply margin of the power system can be fully utilized, enabling all loads to be started to enter the working state at the fastest speed, greatly shortening the ready time of the vehicle functions, improving the user experience, and avoiding unnecessary delays caused by using conservative off-peak startup under safe operating conditions.

[0027] Secondly, this application provides a vehicle, including: The vehicle body domain controller is configured to execute the vehicle control methods described above to control the parallel or staggered startup of each load to be started.

[0028] In the technical solution, by integrating the vehicle control method into the body domain controller, the vehicle has the inherent ability to stably start high-power loads in extremely low temperature environments. As the core of command execution, the vehicle domain controller can autonomously make decisions and precisely schedule the start-up sequence of each load based on the real-time perceived environment and battery status, thereby improving the first-time start-up success rate and system reliability of the vehicle under severe cold conditions, and effectively controlling the cost and complexity of the system.

[0029] As can be seen from the above technical solutions, additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0030] Figure 1 A schematic flowchart illustrating a vehicle control method provided in an embodiment of this application; Figure 2 This is a flowchart illustrating another vehicle control method provided in an embodiment of this application. Detailed Implementation

[0031] In this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0032] The present application will now be described in detail through exemplary embodiments. However, it should be understood that, without further description, elements, structures, and features in one embodiment may be advantageously incorporated into other embodiments. In the current automotive electronic and electrical architecture, the body domain controller, as the integrated control center for vehicle comfort functions, needs to manage multiple high-power loads such as air conditioning, seat heating, door and window control, and lighting. Under normal temperature conditions, vehicle battery voltage is stable, and simultaneous or rapid sequential starting of these loads usually does not cause abnormalities. However, in low-temperature environments of minus 30 degrees Celsius and below, the chemical activity of the battery decreases significantly, leading to increased internal resistance and reduced output capacity. Meanwhile, loads such as positive temperature coefficient heaters used for seat, steering wheel and rear window defrosting will have inrush currents in their resistive components that are much higher than the nominal value at room temperature when starting at low temperatures.

[0033] In existing technologies, the startup control of each load is mostly implemented independently or based on simple timing delays, lacking system-level coordination and forward-looking management; When the vehicle domain controller is in the low-temperature power-on initialization phase, if multiple high-power loads are started simultaneously or quickly according to the preset program, a short-term huge peak power demand will be formed, which will cause the battery output voltage to drop sharply due to the voltage division of internal resistance. If the voltage drops below the minimum operating voltage threshold of the vehicle domain controller and other low-voltage electrical appliances, it may cause the controller to reset, restart, or malfunction, seriously threatening the vehicle's starting safety and reliability under extremely cold conditions.

[0034] Based on this, this application proposes a vehicle control method and a vehicle. By predicting the peak load current and battery internal resistance based on ambient temperature and calculating the lowest voltage point, the starting strategy is intelligently selected accordingly. This achieves adaptive intelligent scheduling of multi-load starting sequence, ensuring voltage stability under low temperature conditions. It solves the problems of system voltage collapse, controller reset, and poor vehicle starting reliability caused by the lack of environmental perception capability in the fixed delay starting strategy in the prior art.

[0035] In the following, embodiments of this application will be described in detail with reference to the accompanying drawings.

[0036] like Figure 1 and Figure 2 As shown in an illustrative embodiment of a vehicle control method according to this application, the method is applied to a vehicle body domain controller, and the control method includes: S1: Obtain the ambient temperature and determine the total peak current of all loads to be started in the load characteristic database corresponding to the ambient temperature based on the ambient temperature; In some embodiments, the ambient temperature is acquired, and the total peak current of all loads to be started in the load characteristic database corresponding to the ambient temperature is determined based on the ambient temperature, including: Based on the ambient temperature, the system queries the preset load characteristic database in the vehicle domain controller to obtain the nominal power and inrush current multiple of each load to be started at the ambient temperature. Based on the nominal power and the inrush current multiple, calculate the inrush current value of each load to be started at the ambient temperature; Based on the inrush current value, calculate the total peak current generated when all loads to be started start simultaneously.

[0037] By establishing a database of load characteristics related to ambient temperature, the accurate quantification of load inrush current was achieved. The load characteristic database pre-stores the nominal power and inrush current multiple of each load to be started under different ambient temperatures, so that the corresponding values ​​can be directly retrieved based on the ambient temperature. The inrush current value and total peak current calculated based on the nominal power and inrush current multiple provide an accurate data basis for subsequent voltage drop prediction, enabling the entire prediction model to have temperature adaptability, thus more accurately reflecting the true electrical characteristics of the load at low temperatures.

[0038] Furthermore, the current real-time ambient temperature is obtained through a high-precision temperature sensor connected to the vehicle domain controller. It can serve as the core input parameter for all subsequent calculations and decisions, and can be directly used to query the characteristics of the load; The characteristics of the load are characterized by a pre-built and stored load characteristic database, located in the non-volatile EEPROM of the vehicle domain controller. This database records in detail the load characteristic parameters of each high-power load under its jurisdiction under different temperature conditions, primarily including the nominal power. and typical inrush current multiple ; For example, for loads like rear window defroster heaters, the load characteristic database indicates that their starting inrush current in extremely cold environments of -30 degrees Celsius can reach 2.5 times their steady-state operating current in normal temperatures of 25 degrees Celsius, i.e., the inrush current multiple. It is 2.5; The load characteristic parameters are not theoretical estimates, but were obtained through extensive and rigorous bench testing and comprehensive calibration in an environmental chamber simulating real low-temperature conditions. This ensures the reliability and accuracy of the data in practical applications and provides solid and reliable data support for the system to perform forward-looking voltage drop prediction and intelligent load start-up management in low-temperature environments.

[0039] Among them, non-volatile memory EEPROM (Electrically Erasable Programmable Read-Only Memory) is a type of electrically erasable programmable read-only memory that combines the characteristics of programmability and non-volatility. Data can be erased and rewritten by applying specific electrical signals, which makes it very convenient for online programming and parameter updates in embedded systems and electronic control units. Inrush current refers to the instantaneous peak current generated by a load, especially a resistive load such as a positive temperature coefficient heater, at the moment of initial power-on from a cold state. This is because the resistance of its internal resistive elements is low at low temperatures, resulting in an instantaneous peak current that is much higher than its normal operating current. Inrush current is the main factor causing system voltage drop. When multiple such resistive loads start simultaneously or successively in a very short time, their instantaneous peak currents will be superimposed, forming a huge instantaneous current demand. When this total current flows through the battery and power supply line with internal resistance, it will generate a significant instantaneous voltage drop across the battery internal resistance and the line impedance. If this voltage drop is too large, causing the power supply bus voltage to be pulled down below the minimum operating voltage threshold of the vehicle domain controller or other critical electrical equipment, it will trigger controller reset, malfunction or system restart, thus posing a system-level risk. Furthermore, based on the obtained ambient temperature of each load to be started... The nominal power below Multiple of impact current Calculate the ambient temperature for each load to be started. The impact current value ; Impact current value The calculation model is as follows:

[0040] in, This is the system's rated operating voltage, typically 12V or 24V; After calculating the inrush current value of each load to be started... Then, the system performs a summation operation to simulate the most extreme case, which is to assume that all loads are activated simultaneously without any timing management. By calculating the impact current values ​​of all individuals By accumulating the data, the system arrives at a theoretical total peak current. This characterizes the maximum instantaneous current requirement that the vehicle's low-voltage power supply network must withstand at the moment of system startup under the current low-temperature environment. Among them, the total peak current The calculation model is as follows:

[0041] Total peak current This represents the peak load that the power network needs to withstand during the startup phase. It is the most direct and important input for subsequent assessment of voltage stability risks. By converting multi-load startup into a quantifiable peak current value, it lays a solid foundation for accurate Ohm's law calculation and voltage drop prediction.

[0042] S2: Use the battery internal resistance model to estimate and determine the corresponding battery internal resistance value; In some embodiments, the internal resistance value of the corresponding battery is estimated and determined using a battery internal resistance model, including: Obtain the battery's state of charge and health status; Based on ambient temperature, state of charge, and health status, the internal resistance value of the battery is obtained by querying a preset battery internal resistance mapping table or by calculating using a preset battery internal resistance empirical calculation model.

[0043] By obtaining the state of charge and health of the battery and combining it with the ambient temperature, the internal resistance value can be estimated using a battery internal resistance mapping table or an empirical calculation model of the battery internal resistance, which significantly improves the estimation accuracy of the internal resistance value. By fully considering multiple dynamic factors affecting the battery's output capability, especially the battery's aging level and remaining charge, the calculated internal resistance value is closer to the battery's actual state under the current low-temperature and harsh operating conditions. This lays a key foundation for accurately predicting system voltage drops and avoids misjudgments in the startup strategy due to inaccurate internal resistance estimation.

[0044] Furthermore, obtaining the state of charge and health status of the battery is a key prerequisite for accurate internal resistance estimation. State of charge and state of health are not fixed or preset values, but dynamic variables estimated by the vehicle battery management system through real-time and continuous monitoring and complex algorithms. As a core unit specifically for managing batteries, the vehicle battery management system continuously collects the battery's terminal voltage, charging and discharging current, and the battery's temperature through its high-precision sensors to obtain multi-dimensional real-time data. Based on multi-dimensional real-time data, the system uses specific estimation algorithms to deduce the state of charge and health status. Among them, the state of charge reflects the percentage of the battery’s current remaining usable capacity relative to its full capacity. Its estimation is usually done by combining the ampere-hour integral method with the open-circuit voltage method and the Kalman filter algorithm. The ampere-hour integration method accumulates the amount of electricity charged or discharged by integrating the current over time. The open-circuit voltage rule uses the known relationship between the voltage at the resting end of the battery and the state of charge to verify and correct the voltage. The Kalman filter algorithm can dynamically and optimally estimate the state of charge by establishing a battery model and fusing multi-source measurement data, and reduce the impact of measurement noise and error.

[0045] Among them, health status characterizes the degree of capacity degradation or performance aging of the battery relative to its brand-new state, and is usually expressed as a percentage. Estimating the health status often requires combining long-term historical operating data, such as tracking capacity changes during a complete charge-discharge cycle, analyzing the trend of internal resistance growth, or modeling voltage response characteristics under specific operating conditions. The health status reflects the irreversible performance degradation of the battery as the usage cycles and calendar life increase.

[0046] These real-time, quantitative states of charge and health obtained through the vehicle battery management system can accurately reflect the battery's true physical condition at the current moment. By using these two key state dimensions along with ambient temperature as input, the subsequent battery internal resistance model can evaluate the battery's actual output capacity and internal losses under the current specific operating conditions from a more comprehensive and dynamic perspective. This greatly improves the accuracy of internal resistance estimation and lays a solid foundation for the reliability of the entire low-temperature start-up strategy.

[0047] Furthermore, the system uses the acquired ambient temperature, state of charge, and health status as joint inputs, and obtains the battery's internal resistance value under the current operating conditions by querying a preset battery internal resistance mapping table or executing a preset battery internal resistance empirical calculation model. ; The battery internal resistance model defines the complete functional requirements and mathematical relationships for dynamically estimating the battery internal resistance based on input parameters. Specifically, it can be a battery internal resistance mapping table or an empirical calculation model for battery internal resistance. Among them, the battery internal resistance mapping table is a multi-dimensional lookup table pre-calibrated based on a large amount of experimental data. It uses ambient temperature, state of charge, and health status as indexes to directly map the corresponding battery internal resistance value. ; For example, a battery internal resistance mapping table may include the internal resistance values ​​of batteries under specific conditions such as minus 30 degrees Celsius, 50% state of charge, and 80% health status. By querying the battery internal resistance mapping table, complex model calculations can be completed offline in advance and stored as discrete data points. During runtime, rapid calculations can be achieved through table lookup and interpolation, directly reflecting the calibration data. The calculation efficiency is high, but it depends on intensive pre-calibration and sufficient storage space.

[0048] Among them, the empirical calculation model of battery internal resistance is a mathematical expression that encapsulates the physical or statistical relationship between the battery's internal resistance value and multiple state parameters. The empirical calculation model for battery internal resistance substitutes the input ambient temperature, state of charge, and health state into a specific empirical formula to calculate and dynamically output the internal resistance value. For example, the empirical calculation model for the internal resistance of a battery is as follows:

[0049] in, The reference internal resistance value usually refers to the internal resistance value of the battery at a reference temperature T0, in a fully charged state, and in a brand new state. It is a basic constant obtained through experimental calibration. The temperature coefficient is a constant greater than 0 determined through data fitting, which determines the sensitivity of the battery's internal resistance to temperature changes. For reference temperature, e.g., 25 degrees Celsius; This is the current temperature of the battery; This represents the current state of charge of the battery, ranging from 0 to 1, where 1 represents a fully charged state. Indicates the degree of battery depletion. The lower, The larger the value; This is the influence coefficient of the state of charge, and its value is greater than 0. It is determined through calibration. This represents the current health status of the battery, with a value ranging from 0 to 1, where 1 represents a brand new state. This indicates the degree of aging of the battery. The lower, The larger the value; The influence coefficient of health status, whose value is greater than 0, is determined through calibration. Whether through a battery internal resistance mapping table or an empirical calculation model of battery internal resistance, the core design reflects the essential characteristic defined by the battery internal resistance model: the internal resistance value is not fixed, but is strongly related to the battery's state of charge, health status, and ambient temperature. Among them, the influence of ambient temperature is particularly significant. The battery internal resistance model ensures that under the same state of charge and health, the lower the temperature, the larger the estimated internal resistance value. This characteristic accurately reflects the physical nature of the battery's reduced output capability at low temperatures due to increased electrolyte viscosity and decreased ion mobility. The accurate internal resistance value obtained through this process is an indispensable key parameter for subsequent reliable prediction of system voltage drop risk.

[0050] S3: Calculate the lowest voltage point when all loads to be started start simultaneously, combining the total peak current, internal resistance, and open-circuit voltage of the battery. In some embodiments, the lowest voltage point when all loads to be started start simultaneously is calculated by combining the total peak current, internal resistance, and open-circuit voltage of the battery, including: The voltage drop when all loads to be started start simultaneously is calculated by multiplying the total peak current by the internal resistance value. The lowest voltage point is obtained based on the difference between the voltage drop amplitude and the open-circuit voltage of the battery.

[0051] By combining the predicted total peak current with the estimated battery internal resistance and calculating the theoretical voltage drop based on Ohm's law, the lowest voltage point can be determined. This transforms abstract current and internal resistance parameters into intuitive voltage risk prediction values, enabling the system to quantitatively assess voltage stability under the worst operating conditions. By comparing the theoretical minimum voltage with the open-circuit voltage, potential voltage collapse risks can be identified in advance, providing a clear and reliable quantitative basis for the dynamic selection of startup strategies, and achieving a key leap from parameter perception to risk prediction.

[0052] Furthermore, the calculated total peak current Compared with the internal resistance value of the battery estimated through the internal model of the battery. By substituting all these values ​​into Ohm's law, we can predict the voltage drop that the power supply network might experience in the worst-case scenario where all loads to be started are activated simultaneously. ; The calculation model for Ohm's law formula is as follows:

[0053] The calculation of voltage sag amplitude enables the conversion from multiple dispersed load inrush currents and an internal parameter characterizing power supply capability to a unified, assessable voltage sag value, thus transforming this system-level risk indicator. At the moment when the vehicle domain controller completes its basic self-test and enters the load management program initialization, and before all high-power loads are enabled, obtaining the current open-circuit voltage of the battery can ensure that the power supply network is in a near-no-load quasi-open-circuit state. At this time, the terminal voltage measured from the positive and negative terminals of the battery is least affected by the ohmic voltage drop caused by the load current, and its value is closest to the true open-circuit voltage. The open-circuit voltage can be obtained by actively requesting or passively receiving battery status messages periodically broadcast by the battery management system through the vehicle controller local area network bus. As a professional monitoring unit, the battery management system usually provides voltage data that has been filtered and compensated, and has high authority. The open-circuit voltage can also be obtained by direct measurement through a high-precision analog-to-digital converter connected to the main power supply line on the vehicle domain controller. It can complete a voltage sampling in milliseconds and directly obtain the instantaneous voltage value at the controller power input terminal. In engineering practice, the system can prioritize the use of data provided by the battery management system and cross-validate it with the measurement values ​​of local sensors. If the difference between the two is within a reasonable tolerance, the data is confirmed to be valid. If there is a significant deviation or a signal fails, the backup data source is activated and the relevant diagnostic events are recorded. The above method can be used to obtain the raw voltage data, and then the system will perform a reasonableness judgment and filtering on the raw voltage data. For example, it is determined whether the original voltage data is within the possible physical voltage range of the battery, and a short-time digital filter may be applied to smooth out possible sampling noise. The stable voltage value after this processing is finally confirmed as the open-circuit voltage used for prediction calculation. The verified reference voltage, together with the predicted voltage drop, constitutes the basis of risk assessment, ensuring the reliability of subsequent decisions. After obtaining the predicted voltage drop magnitude Then, the system combines the real-time acquired open-circuit voltage of the battery to calculate the predicted minimum voltage point. The calculation model for the lowest voltage point is as follows:

[0054] in, This is the lowest voltage point; This is the open-circuit voltage; By combining the predicted voltage drop magnitude with the current open-circuit voltage of the battery, the final output is an absolute value representing the lowest possible voltage that the system can reach at startup, providing an accurate input for subsequent direct comparison with a fixed safety threshold.

[0055] For example, in the current low temperature environment of minus 25 degrees Celsius, the system calculates the total peak current when the seat heater, steering wheel heater, and rear window defroster heater are started simultaneously by querying the load characteristic database. It is 150A; Meanwhile, based on the current temperature environment, the battery's state of charge of 60%, and its health status of 85%, the current internal resistance value of the battery is estimated using a battery internal resistance model. Given an impedance of 20mΩ, according to Ohm's law, the predicted voltage drop is... ; The actual open-circuit voltage of the battery is obtained in real time through the battery management system or local sensors. It is 12.5V; Predicted system minimum voltage point .

[0056] S4: Compare the lowest voltage point with the preset safe voltage threshold to obtain the comparison result, and determine the starting strategy of the load to be started as either off-peak starting or parallel starting based on the comparison result; In some embodiments, the lowest voltage point is compared with a preset safe voltage threshold to obtain a comparison result. Based on the comparison result, the startup strategy for the load to be started is determined to be either off-peak startup or parallel startup, including: If the lowest voltage point is less than the preset safe voltage threshold, the startup strategy is off-peak startup; If the lowest voltage point is greater than or equal to the safe voltage threshold, the startup strategy is parallel startup.

[0057] By directly comparing the predicted minimum voltage point with the safe voltage threshold, when the minimum voltage point is lower than the safe voltage threshold, a peak-shifting startup strategy is automatically triggered to avoid risks; otherwise, an efficient parallel startup strategy is adopted. This makes the selection of startup strategy no longer fixed or blind, but based on the quantitative assessment of the contradiction between the current system power supply capacity and load demand. This achieves adaptive switching of startup mode, maximizing startup efficiency while ensuring system safety, and balancing reliability and timeliness.

[0058] Furthermore, the system executes explicit decision-making logic based on the quantitative comparison results. If the calculated predicted minimum voltage point is greater than the preset safe voltage threshold, the system determines that under the current ambient temperature, battery status and load combination, the power system has sufficient redundancy to withstand the impact of all loads starting at the same time, and the risk of voltage drop is low. At this point, the system will adopt the standard parallel start mode, that is, send enable signals to the drive circuits of all loads to be started almost simultaneously, so that functions such as air conditioning, seat heating, and headlights can enter the ready state as quickly as possible, thereby maximizing the user's initial experience and functional availability.

[0059] If the predicted minimum voltage point is less than the safe voltage threshold, the system determines that there is a clear risk of voltage collapse and directly triggers and executes the off-peak start-up strategy. For example, assuming the preset safe voltage threshold is 9.6V, under a certain operating condition, the system predicts the lowest voltage point to be 9.8V. At this time, the lowest voltage point is higher than the safe voltage threshold, so the startup strategy is parallel startup, and all loads to be started are powered on within about 100ms. Under another, more severe low-temperature operating condition, the predicted minimum voltage point is 9.4V. At this point, the minimum voltage point is lower than the safe voltage threshold, and the system immediately rejects the parallel start-up plan and starts the peak-shifting management process instead. It should be noted that the safe voltage threshold is a lower limit of voltage protection set to ensure that the vehicle domain controller and critical on-board electronic equipment can still work stably under extreme conditions. The safe voltage threshold is determined by the fact that it must be higher than the minimum operating voltage of all protected devices in the system, especially the reset voltage of the body domain controller itself. For example, if the reset voltage of the vehicle domain controller is 9.0V, considering uncertainties such as line voltage drop, measurement error and transient interference, a design margin must be added on this basis to cope with voltage fluctuations and parameter drift that may occur in actual applications, and to ensure that the system can still maintain sufficient protection buffer under the worst conditions. Therefore, the safe voltage threshold may be set to 9.6V, which is the absolute benchmark for the system to judge voltage stability risks. When the predicted or monitored lowest voltage point is lower than this safe voltage threshold, the system will determine it as a high-risk state and immediately activate protective measures. A clear definition of the safe voltage threshold is crucial for understanding the decision-making logic of the entire scheme and serves as a robust defense for the electrical safety design of the entire system.

[0060] By conducting real-time risk assessments based on the specific system state at each power-on and making startup decisions that best match the current safety margin, startup failures caused by changes in conditions are eliminated at the source.

[0061] S5: Determine the startup time of the load to be started based on the startup strategy, and control the startup of each load to be started based on the startup time.

[0062] In some embodiments, the startup time of the loads to be started is determined based on a startup strategy, and the startup of each load to be started is controlled based on the startup time, including: If the startup strategy is off-peak startup, then each load to be started is sorted based on the preset safety priority and inrush current value to obtain a load startup order list; Based on the load startup order list, a preset delay time is inserted between loads to be started with different security priorities; Based on the load startup sequence list and delay time, the vehicle body domain controller sequentially controls the drive circuits of each load to be started to output enable signals, so that each load to be started can start in staggered shifts.

[0063] After determining to adopt staggered start-up, a two-dimensional sorting mechanism based on safety priority and inrush current value was introduced to generate a load start-up sequence, ensuring that key functions related to driving safety are started first. By inserting configurable delays between different priority groups, the simultaneous startup of multiple high-current loads in a short period of time is effectively avoided. The loads are driven sequentially according to the generated precise timing sequence, which realizes the dispersion of power peaks on the time axis and ensures a smooth transition of system voltage.

[0064] In some embodiments, if the startup strategy is off-peak startup, the loads to be started are sorted based on preset safety priorities and inrush current values ​​to obtain a load startup order list, including: All loads to be started are grouped and sorted according to their security priority. Within the same safety priority group, loads are sorted according to the magnitude of their inrush current values ​​to obtain a load start-up order list.

[0065] By sorting inrush currents by magnitude within the same priority group, smooth transition management of inrush currents is achieved, ensuring the core requirement of functional safety and enabling high-priority loads to receive power supply first. Under the premise of meeting safety requirements, by arranging the loads within the group in ascending order of inrush current, the current surge introduced by each startup is minimized, which is conducive to the voltage recovery of the power supply network. An optimal balance can be achieved between safety and smoothness, so that the generated startup sequence not only meets functional safety requirements, but also minimizes the instantaneous pressure on the power supply system.

[0066] Furthermore, the load startup sequence list is a software scheduling strategy executed by the vehicle domain controller. Based on the safety priority and inrush current characteristics of the loads, this software scheduling strategy allocates different startup times to different loads or load groups. By inserting controllable delays on the time axis, the instantaneous power peaks generated when each load starts are staggered in time, thereby ensuring that the total instantaneous power demand of the system never exceeds the safe power supply capacity of the power network under the current operating conditions, so as to maintain the stability of the bus voltage.

[0067] To ensure a smooth and orderly startup process, the system implements refined load management and timing orchestration. The system defines two key attributes for each load: safety priority and inrush current level. Safety priority refers to assigning the highest priority to functions related to driving safety and regulatory compliance. For example, external lights are used to ensure vehicle visibility and have the highest priority; seat heating and steering wheel heating, which are comfort functions, have the next highest priority; while functions such as rear window defrosting, although important, are not immediately necessary and their activation can be appropriately delayed. The inrush current level is sorted according to the inrush current value of the load to be started at the current ambient temperature under the same safety priority. The load to be started with the smaller inrush current value is started first. This helps the system voltage to transition smoothly and avoids unnecessary superimposed peaks within the group. When the system determines that staggered startup is required, all loads to be started are first sorted according to the rules of the two dimensions mentioned above. The loads are sorted in descending order of safety priority, and then in ascending order of inrush current value within the same priority group. Subsequently, a software-configurable fixed delay is inserted between load groups of different priorities. For example, a delay T1 of 100ms is inserted between the highest priority group and the second highest priority group, and a delay T2 of 150ms is inserted between the second highest and lower priority groups. The delay time setting must ensure that the peak inrush current of the preceding load group has basically subsided and the power supply network voltage has returned to a stable level, thereby providing a safe voltage platform for the start-up of the next load group; For example, in low-temperature environments, the loads to be started include low beam headlights, position lights, seat heaters, steering wheel heaters, and rear window defroster heaters; According to the preset rules, low beam headlights and position lights have the highest safety priority; heated seats and heated steering wheel have the second highest safety priority; and rear window defroster has the lowest safety priority.

[0068] The safety priority of the load to be started is not dynamically generated at runtime, but is established based on the top-level design of the vehicle's electronic and electrical architecture through a set of predefined and solidified static rules in the software. The vehicle domain controller software integrates a predefined load management configuration data, which exists in the form of a lookup table or a structured parameter set, permanently binding each controllable load to be started with a defined security priority code. For example, in the load management configuration data, low beam headlights and position lights are associated with codes representing the highest safety priority. This definition directly reflects their fundamental attributes as the core of the lighting system, which are related to active driving safety and regulatory compliance. Similarly, seat heaters and steering wheel heaters are associated with the second-highest safety priority code, reflecting their important support for drivers to maintain operational comfort and focus in extreme environments; The rear window defroster heater is associated with a normal safety priority code, because although its function is important, a slight delay is allowed when system resources are scarce; When the startup strategy is off-peak startup, the dynamic sequence generation algorithm will directly call this fixed load management configuration data. First, it will traverse all loads to be started and obtain their respective preset priority codes from the load management configuration data by querying their identifiers. The load start order is formed by sorting the loads in descending order based on their priority codes, thus creating a list of load start orders based on security priority groups. For example, all the highest security priority codes are assigned to the first startup group, the second highest security priority codes are assigned to the second group, and so on. Within this framework, the inrush current value is introduced as a secondary criterion for group ranking. By combining immutable safety rules with real-time changing electrical parameters, the system ensures that the startup behavior always adheres to the most fundamental safety and regulatory bottom line, while also enabling fine-tuning based on the current specific electrical environment, thereby achieving an optimal balance between safety and stability.

[0069] Within the highest safety priority group, if the inrush current value of the low beam headlight is 8A and the inrush current value of the position light is 5A, then the order is to start the position light first, and then start the low beam headlight. Within the second-highest priority group, if the steering wheel heating inrush current is 25A and the seat heating inrush current is 30A, then the order is to start the steering wheel heating first, and then start the seat heating. The final generated load start sequence list and delay time are as follows: first, the position lights are started, followed by the low beam headlights; after a preset delay time T1, the steering wheel heater is started; then, after a short interior interval, the seat heaters are started; finally, after another preset delay time T2, the rear window defroster heater is started. By employing this refined sequencing and delayed insertion, the system decomposes the potentially simultaneous massive total inrush current into multiple sequentially occurring, smaller current steps with controlled amplitudes. This maximizes the maintenance of voltage stability in the power supply network while meeting the functional safety startup sequence, achieving an optimized balance between reliability and efficiency.

[0070] In some embodiments, if the startup strategy is parallel startup, the vehicle domain controller simultaneously outputs enable signals to the drive circuits of all loads to be started, so that all loads to be started can be started in parallel.

[0071] By simultaneously outputting enable signals to all load drive circuits after determining parallel startup, the power supply margin of the power system can be fully utilized, enabling all loads to be started to enter the working state at the fastest speed. This greatly shortens the ready time of the vehicle functions, improves the user experience, and avoids unnecessary delays caused by using conservative off-peak startup under safe operating conditions.

[0072] Furthermore, the execution of the parallel startup strategy means that the system determines that the voltage stability risk of the current power supply network is low and has the ability to simultaneously bear the inrush current of all loads. Under the parallel startup strategy, the vehicle domain controller will bypass the complex timing orchestration logic and directly enter the high-efficiency execution stage. In essence, the vehicle domain controller generates and sends out control signals corresponding to all loads to be started almost synchronously within a very short time window on its internal drive chip or power output channel. The control signal can be a pulse width modulation waveform that drives the high-side switch to close, or a digital level that triggers the relay to engage. All loads receive power and begin the startup process at almost the same time. For example, in scenarios where the temperature is not low or the battery is in excellent condition, the ambient temperature is 15°C, the battery's state of charge is 90%, and its health status is 95%. After the system executes the aforementioned prediction process, it calculates that the predicted lowest voltage point is 11.5V, which is much higher than the safe voltage threshold of 9.6V. Based on this quantitative evaluation result, the system decision adopts a parallel start strategy. Subsequently, within a few milliseconds, the body domain controller synchronously sends enable commands to the drive modules of multiple loads such as low beam headlights, position lights, seat heaters, steering wheel heaters, and air conditioning blowers. These loads then start up simultaneously, and the total current formed by the superposition of their inrush currents is still within the safe tolerance range of the power supply system. Once the vehicle is powered on, the external lighting, main interior heating and ventilation functions are all ready in a very short time. Users do not need to experience any waiting due to the sequential activation of functions, achieving a seamless and smooth startup experience. This reflects the principle of maximizing the exploitation and utilization of system performance potential while ensuring absolute safety, thereby dynamically providing optimal startup efficiency in different environments and states.

[0073] Based on the above vehicle control method, a dynamic correlation mechanism between load characteristics and temperature is established. The total peak current and battery internal resistance are predicted with ambient temperature as the core parameter. Risk-based adaptive selection of starting strategy is achieved through voltage prediction, transforming the traditional static starting logic into an intelligent decision-making process based on real-time state perception. By proactively predicting and optimizing decisions, the risk of voltage collapse caused by the simultaneous startup of multiple loads can be effectively avoided, significantly improving the startup reliability and stability of vehicle electronic systems in low-temperature scenarios.

[0074] In some embodiments, based on a load startup sequence list and a delay time, the vehicle domain controller sequentially controls the drive circuits of each load to be started to output enable signals, so that each load to be started can be started in staggered shifts, including: Real-time monitoring of the actual voltage of the power supply network bus; If the actual voltage drop is lower than the safety threshold, the delay time will be shortened to the first delay time. If the actual voltage drop exceeds the safety threshold, the delay time will be extended to the second delay time or the startup of the load to be started will be suspended.

[0075] By introducing a dynamic delay adjustment mechanism based on actual voltage monitoring during the off-peak start-up process, the system no longer mechanically executes the preset delay, but can be optimized in real time according to the actual response of the power supply network. When the voltage drop is detected to be below the safety threshold, the startup process is accelerated and efficiency is improved by shortening the subsequent delay. When the voltage drop is abnormal or the recovery is slow, the startup is provided with stronger protection by extending the delay or pausing the startup process. This enhances the system's adaptability to uncertainties such as different battery states and line impedances, and further improves the robustness and safety of the startup process.

[0076] Furthermore, the vehicle domain controller, as the core execution unit, strictly follows the generated load startup sequence list and delay time, and enables the power path of each load sequentially and precisely through its internal integrated drive chip or independent power switching device. Within the critical time window after each group or load starts, the body domain controller continuously samples the actual voltage of the power supply bus through its high-precision analog-to-digital converter and compares it with the reference voltage before startup, and calculates the drop and recovery of the actual voltage in real time. If the actual voltage drop detected is much smaller than the safety threshold, and the actual voltage recovers quickly and stably before the preset delay ends, this indicates that the actual performance of the battery and circuit is better than the conservative estimate of the battery internal resistance model, and the current electrical environment is relatively relaxed. At this point, the system can proactively decide to dynamically shorten the fixed delay between subsequent load groups to be started to a shorter first delay time, such as from the preset 100ms to 50ms, thereby accelerating the entire startup sequence and completing all functions ready faster. If the actual voltage drop exceeds the safety threshold, or the voltage recovery is abnormally slow, this indicates that there may be unforeseen circumstances, such as insufficient instantaneous output capacity of the battery or abnormally increased line contact resistance. As a protective response, the system will immediately take defensive measures, dynamically extending the subsequent delay to a longer second delay time, such as from 100ms to 200ms, to give the power supply network more time to recover; or in extreme cases, directly suspending the startup sequence, interrupting the enabling of subsequent loads, and at the same time reporting specific fault codes through the diagnostic interface to indicate that there is a potential electrical problem in the system.

[0077] For example, after executing the load start-up sequence to the steering wheel heater, the system detected that the actual voltage drop was only 0.3V and recovered within 50ms, lower than the predicted 0.8V drop and the preset delay of 100ms. The system automatically shortened the originally planned 100ms internal interval before the seat heater started to 50ms; If, after starting the low beam headlights, the actual voltage drops by 1.5V and fails to return to a safe level for more than 150 ms, the system will determine that there is an anomaly and delay the start of subsequent position lights by 200 ms, or, if there are continuous anomalies, suspend the entire sequence and report a fault code indicating abnormal voltage during the start-up process. Through the aforementioned closed-loop monitoring and dynamic adjustment mechanism, the startup strategy possesses strong environmental adaptability and fault tolerance, ensuring the safety and reliability of the startup process even when there are deviations in model predictions or uncalibrated changes in system state.

[0078] This application also provides a vehicle, including: The vehicle body domain controller is configured to execute the vehicle control methods described above to control the parallel or staggered startup of each load to be started.

[0079] By integrating the vehicle's control methods into the body domain controller, the vehicle is endowed with the inherent ability to stably start high-power loads in extremely low temperature environments. As the core of command execution, the vehicle domain controller can autonomously make decisions and precisely schedule the start-up sequence of each load based on the real-time perceived environment and battery status, thereby improving the first-time start-up success rate and system reliability of the vehicle under severe cold conditions, and effectively controlling the cost and complexity of the system.

[0080] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A vehicle control method, applied to a vehicle body domain controller, characterized in that, The method includes: Obtain the ambient temperature, and based on the ambient temperature, determine the total peak current of all loads to be started in the load characteristic database corresponding to the ambient temperature; The internal resistance value of the corresponding battery is estimated and determined using the battery internal resistance model; By combining the total peak current, the internal resistance value, and the open-circuit voltage of the battery, calculate the lowest voltage point when all loads to be started start simultaneously; The lowest voltage point is compared with a preset safe voltage threshold to obtain a comparison result. Based on the comparison result, the startup strategy of the load to be started is determined to be either off-peak startup or parallel startup. The startup time of the load to be started is determined based on the startup strategy, and the startup of each load to be started is controlled based on the startup time.

2. The vehicle control method according to claim 1, characterized in that, Obtain the ambient temperature, and based on the ambient temperature, determine the total peak current of all loads to be started in the load characteristic database corresponding to the ambient temperature, including: Based on the ambient temperature, the load characteristic database preset in the vehicle domain controller is queried to obtain the nominal power and inrush current multiple of each load to be started at the ambient temperature; Based on the nominal power and the inrush current multiple, calculate the inrush current value of each of the loads to be started at the ambient temperature; Based on the inrush current value, calculate the total peak current generated when all loads to be started start simultaneously.

3. The vehicle control method according to claim 2, characterized in that, The internal resistance value of the battery is estimated and determined using a battery internal resistance model, including: Obtain the state of charge and health status of the battery; Based on the ambient temperature, the state of charge, and the health status, the internal resistance value of the battery is obtained by querying a preset battery internal resistance mapping table or by calculating using a preset battery internal resistance empirical calculation model.

4. The vehicle control method according to claim 3, characterized in that, Based on the total peak current, the internal resistance, and the open-circuit voltage of the battery, calculate the lowest voltage point when all loads to be started simultaneously, including: The voltage drop when all loads to be started start simultaneously is calculated by multiplying the total peak current by the internal resistance value. The lowest voltage point is obtained based on the difference between the voltage drop amplitude and the open-circuit voltage of the battery.

5. The vehicle control method according to claim 1, characterized in that, The lowest voltage point is compared with a preset safe voltage threshold to obtain a comparison result. Based on the comparison result, the startup strategy for the load to be started is determined to be either off-peak startup or parallel startup, including: If the lowest voltage point is less than the preset safe voltage threshold, then the startup strategy is off-peak startup; If the lowest voltage point is greater than or equal to the safe voltage threshold, then the startup strategy is parallel startup.

6. The vehicle control method according to claim 5, characterized in that, The startup time of the loads to be started is determined based on the startup strategy, and the startup time of each load to be started is controlled based on the startup time, including: If the startup strategy is off-peak startup, then each load to be started is sorted based on the preset safety priority and the inrush current value to obtain the load startup order list; Based on the load startup order list, a preset delay time is inserted between the loads to be started with different security priorities; Based on the load startup sequence list and the delay time, the vehicle domain controller sequentially controls the drive circuits of each load to be started to output enable signals, so that each load to be started can be started in staggered shifts.

7. The vehicle control method according to claim 6, characterized in that, If the startup strategy is off-peak startup, then the loads to be started are sorted based on the preset safety priority and the inrush current value to obtain the load startup order list, including: All loads to be started are grouped and sorted according to the security priority order. Within the same safety priority group, the loads are sorted according to the magnitude of their inrush current values ​​to obtain a load start-up order list.

8. The vehicle control method according to claim 6, characterized in that, Based on the load startup sequence list and the delay time, the vehicle domain controller sequentially controls the drive circuits of each load to be started to output enable signals, so that each load to be started can be started in staggered shifts, including: Real-time monitoring of the actual voltage of the power supply network bus; If the actual voltage drop is lower than the safety threshold, the delay time is shortened to the first delay time. If the actual voltage drop exceeds the safety threshold, the delay time will be extended to a second delay time or the startup of the load to be started will be suspended.

9. The vehicle control method according to claim 5, characterized in that, If the startup strategy is parallel startup, then the vehicle domain controller will simultaneously output enable signals to the drive circuits of all loads to be started, so that all loads to be started can be started in parallel.

10. A vehicle comprising: A vehicle body domain controller is configured to perform the vehicle control method as described in any one of claims 1 to 9 to control the parallel or staggered startup of each load to be started.

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