Vehicle power supply control method and device, vehicle-mounted equipment, vehicle and storage medium

Abstract

A vehicle power supply control method and device, a vehicle-mounted equipment, a vehicle and a storage medium are disclosed, and relate to the technical field of vehicle power supply control. The method comprises: obtaining a power consumption demand parameter of the vehicle; predicting a target power consumption required by the vehicle in a parking scenario according to the power consumption demand parameter and the health status of each power supply equipment of the vehicle; and controlling the target power supply equipment supporting the output target power consumption to supply power to the vehicle according to the target power consumption and the output power interval supported by each power supply equipment. The present scheme realizes dynamic and accurate decision of the power supply path in the parking scenario, effectively reduces energy consumption and improves power supply stability.

Description

Technical Field

[0001] This application relates to the field of vehicle power supply control, and more specifically, to a vehicle power supply control method, apparatus, on-board equipment, vehicle, and storage medium. Background Technology

[0002] As vehicles become increasingly electrified, they support a wider range of functions when parked, such as sentry mode, remote control, and data uploading. To address the risks of low-voltage battery depletion and the low conversion efficiency and high energy loss of high-power converters under low load conditions when vehicles are parked, one solution is to introduce auxiliary power supply equipment. This equipment uses a fixed power threshold to switch to low-voltage system power. However, this method cannot adapt to the fluctuating parking load and changes in the power supply's own state, easily leading to inaccurate power supply decisions, energy waste, or insufficient power supply stability. Summary of the Invention

[0003] In view of this, embodiments of this application propose a vehicle power supply control method, apparatus, on-board equipment, vehicle, and storage medium to improve the above-mentioned problems.

[0004] According to a first aspect of the embodiments of this application, a vehicle power supply control method is provided, the method comprising: acquiring power consumption demand parameters of a vehicle; the power consumption demand parameters indicating the power consumption level of the vehicle in a parking scenario; predicting a target power consumption required by the vehicle in the parking scenario based on the power consumption demand parameters and the health status of each power supply device of the vehicle; the health status indicating the state of charge and health of the power supply device; and controlling a target power supply device that supports outputting the target power consumption to supply power to the vehicle based on the target power consumption and the output power range supported by each power supply device; wherein the target power consumption belongs to the output power range supported by the target power supply device.

[0005] In some embodiments, each of the power supply devices includes: a first converter, a second converter, and a battery; the output power range includes an upper power limit and a lower power limit, the lower power limit of the first converter is greater than or equal to the upper power limit of the second converter, and the lower power limit of the second converter is greater than or equal to the upper power limit of the battery; the step of controlling a target power supply device that supports outputting the target power consumption to supply power to the vehicle according to the target power consumption and the output power range supported by each of the power supply devices includes: controlling the first converter to supply power when the target power consumption reaches the lower power limit of the first converter; controlling the second converter to supply power when the target power consumption reaches the lower power limit of the second converter but does not reach the upper power limit of the second converter; and controlling the battery to supply power when the target power consumption does not reach the lower power limit of the second converter.

[0006] In some embodiments, the method further includes: switching to the first converter for power supply in the event of a failure of the second converter.

[0007] In some embodiments, the power consumption requirement parameters include current power consumption requirement, historical statistical power consumption, and limit power consumption. Predicting the target power consumption required by the vehicle in the parking scenario based on the power consumption requirement parameters and the health status of the power supply equipment of each vehicle includes: determining the weight corresponding to each power consumption requirement parameter based on the health status; and calculating the target power consumption based on each power consumption requirement parameter and its corresponding weight.

[0008] In some embodiments, the method further includes: monitoring the actual power consumption of the vehicle, and if the actual power consumption is greater than or equal to the output power range of the target power supply device, switching to a power supply device with a higher output power range for power supply.

[0009] In some embodiments, the method further includes updating the weights corresponding to each of the power consumption requirement parameters based on the actual power consumption.

[0010] According to a second aspect of the embodiments of this application, a vehicle power supply control device is provided. The device includes: an acquisition module, configured to acquire power consumption demand parameters of a vehicle; the power consumption demand parameters are used to indicate the power consumption level of the vehicle in a parking scenario; a prediction module, configured to predict the target power consumption required by the vehicle in the parking scenario based on the power consumption demand parameters and the health status of each power supply device of the vehicle; the health status is used to indicate the state of charge and health of the power supply device; and a control module, configured to control a target power supply device that supports outputting the target power consumption to supply power to the vehicle based on the target power consumption and the output power range supported by each power supply device; the target power consumption belongs to the output power range supported by the target power supply device.

[0011] According to a third aspect of the embodiments of this application, an in-vehicle device is provided, including: a processor; a memory, wherein computer-readable instructions are stored on the memory, and when the computer-readable instructions are executed by the processor, the vehicle power supply control method described above is implemented.

[0012] According to a fourth aspect of the embodiments of this application, a vehicle is provided, including: a body, a plurality of power supply devices and an on-board device as described above; each of the power supply devices is disposed inside the body, and the on-board device is connected to each of the power supply devices.

[0013] According to a fifth aspect of the embodiments of this application, a computer-readable storage medium is provided that stores computer-readable instructions thereon, which, when executed by a processor, implement the vehicle power supply control method as described above.

[0014] According to a sixth aspect of the present application, a computer program product is provided, the computer program product including computer instructions stored in a computer-readable storage medium; the computer instructions are read and executed by a processor of a computer device to implement the vehicle power supply control method as described above.

[0015] In this application, the solution obtains power consumption demand parameters and predicts the target power consumption based on the health status of the power supply equipment. Then, it performs matching control according to the output power range supported by each power supply equipment, overcoming the shortcomings of traditional static threshold decision-making which cannot adapt to power state decay and load fluctuations. In weak states such as battery aging or low battery levels, it can automatically correct power consumption expectations and select a more reliable power supply path, effectively preventing unexpected power outages or system crashes caused by overestimating power supply capacity. This significantly improves the accuracy of power supply decisions and the robustness of the system in parking scenarios.

[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit the embodiments of this application. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0018] Figure 1 This is a structural diagram of a vehicle power supply system based on existing technology; Figure 2 This is a schematic diagram of the structure of a vehicle power supply control system according to an embodiment of this application; Figure 3 This is a schematic flowchart illustrating a vehicle power supply control method according to an embodiment of this application; Figure 4 This is a schematic flowchart illustrating a vehicle power supply control method according to another embodiment of this application; Figure 5 This is a schematic flowchart illustrating a vehicle power supply control method according to another embodiment of this application; Figure 6 This is a schematic flowchart of a vehicle power supply control method according to another embodiment of this application; Figure 7 This is a block diagram of a vehicle power supply control device according to an embodiment of this application; Figure 8 This is a hardware structure diagram of an in-vehicle device according to an embodiment of this application; Figure 9 This is a hardware structure diagram of a vehicle according to an embodiment of this application.

[0019] The accompanying drawings have illustrated specific embodiments of the present application. More detailed descriptions will follow. These drawings and descriptions are not intended to limit the scope of the present application's embodiments in any way, but rather to illustrate the concepts of the present application's embodiments to those skilled in the art through specific embodiments. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0021] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0022] Before providing a detailed explanation of the vehicle power supply control method provided in the embodiments of this application, the application scenarios provided in the embodiments of this application will be introduced first.

[0023] As the electrification level of hybrid vehicles increases, the functions that need to be supported in the parked state are becoming increasingly diverse, such as sentry mode, remote control, and data uploading. Traditional hybrid vehicles rely on a high-power DC-DC converter to draw power from the high-voltage battery to supply power to the low-voltage system when in the OFF position.

[0024] However, existing technologies have the following serious defects and shortcomings: Low energy efficiency: The conversion efficiency of high-power DC-DC converters drops significantly under low load conditions. In parking scenarios, the power consumption of the entire vehicle is usually less than 200W, but the high-voltage system still needs to be kept running, resulting in unnecessary energy loss. For example, in sentry mode, only a few controllers such as the intelligent driving camera and the large screen need to work, but traditional solutions need to wake up the three-electric system and close the high-voltage relay, causing no-load loss of high-voltage components.

[0025] Range loss: The continuous operation of the high-voltage system will consume the power battery, especially for hybrid vehicles. The high-voltage battery capacity is limited, and frequent activation of the three-electric system will significantly shorten the pure electric range.

[0026] Risk of small battery depletion: The low-voltage system relies on a 12V small battery for power. If the parking function is used frequently, the small battery is prone to depletion, which may cause the vehicle to fail to start or malfunction.

[0027] like Figure 1 As shown, Figure 1 This is a schematic diagram of the existing vehicle power supply system architecture. In the existing hybrid vehicle power supply architecture, the high-voltage power battery pack only contains high-voltage cells (series modules) and a Battery Management System (BMS) module. The positive and negative terminals of the high-voltage cells are led out through the high-voltage bus (HV+, HV-) to a high-power DC-DC converter outside the battery pack. The rated power of the high-power DC-DC converter is typically 2kW to 3kW. Its input is connected to the high-voltage bus, and its output is connected to the low-voltage bus, converting the high-voltage DC power to 12V low-voltage DC power to power various functional controllers connected in parallel on the low-voltage bus (such as the Vehicle Control Unit (VCU), Electronic Control Unit (ECU), Body Control Module (BCM), On-Board Charger (OBC), Transmission Control Unit (TCU), and In-Vehicle Information Processing Unit (In). The vehicle head unit (IHU) supplies power to the system. A low-voltage battery (typically a 12V lead-acid battery) is connected in parallel to the low-voltage bus as an energy buffer and emergency backup power source. In this architecture, when the vehicle is in the OFF parking position, even if only low-power functions such as sentry mode (typically less than 200W) require power, the entire electric drive system must be activated and the high-voltage relay closed, allowing the high-power DC-DC converter to draw power from the high-voltage battery pack. However, the high-power DC-DC converter's conversion efficiency drops significantly under low-load conditions, and maintaining the electric drive system in a high-voltage standby state itself generates unnecessary static power consumption, resulting in significant energy waste. Furthermore, frequent activation of the electric drive system consumes high-voltage battery power, shortening the pure electric driving range and increasing the risk of low-voltage battery depletion.

[0028] like Figure 2 As shown, Figure 2 This is a schematic diagram of the vehicle power supply control system architecture according to an embodiment of this application. Figure 1 Compared to the existing technology, the core improvement of this application lies in the integration of a low-power DC-DC converter (rated power ≤200W) within the high-voltage battery pack. Its input is directly connected across the high-voltage cells inside the battery pack, and its output is connected to the low-voltage bus. The low-power DC-DC converter and the BMS module establish signal interaction via a Controller Area Network (CAN) communication link. The BMS module controls the start and stop of the low-power DC-DC converter via hard-wired signals and performs fault diagnosis and data recording. The high-voltage battery pack also includes a power management module, which is responsible for real-time statistics, recording, and dynamic prediction of the total power consumption of the parking function, and determines the power supply path based on the prediction results. The power management module has a built-in power prediction algorithm unit, including a historical power consumption database and a machine learning model. A high-voltage relay is also provided on the high-voltage bus (HV+) to control the connection and disconnection between the high-power DC-DC converter and the high-voltage battery pack. On the low-voltage bus side, each functional controller's power supply branch is equipped with an electronic fuse. This electronic fuse acts as an intelligent power distribution execution unit, controlled by the power management module. In conjunction with local network management, it only powers and wakes up the target controller, not the entire vehicle network. The low-voltage battery uses a 12V lithium battery, compared to... Figure 1Lead-acid batteries, as described above, offer advantages such as high energy density, long cycle life, and low self-discharge rate. Through the aforementioned architecture design, in low-power parking scenarios, the BMS module can hardwire-wake up a low-power DC-DC converter for independent power supply, eliminating the need to wake up the three-electric system and the high-power DC-DC converter. This avoids no-load losses in the high-voltage system and significantly reduces energy consumption in parking scenarios. Simultaneously, the power management module intelligently determines the power supply path based on power consumption prediction results, working with electronic fuses to achieve precise on-demand power distribution, forming a closed-loop control mechanism of "prediction-decision-monitoring-correction."

[0029] like Figure 3 As shown, this embodiment provides a vehicle power supply control method. This method is mainly applied to the power management process when the vehicle is parked, aiming to solve the problems of energy waste or insufficient power supply stability caused by static decision-making in the prior art. In specific embodiments, this vehicle power supply control method can be applied to, for example... Figure 7 The vehicle power supply control device 300 and the on-board equipment 400 equipped with the vehicle power supply control device 300 are shown. Figure 8 The specific process of this embodiment will be described below. Of course, it is understood that this method can be executed by an electronic device with computing power. The electronic device is connected to multiple power supply devices in the vehicle. The specific type of electronic device is not limited and can be configured according to actual application requirements. For example, in one alternative example, the electronic device may include an in-vehicle device. In another alternative example, the electronic device may include a vehicle-mounted server, a cloud server, or other processors, etc. The following will focus on... Figure 3 The process shown is described in detail. The vehicle power supply control method may specifically include the following steps S110-S130.

[0030] Step S110: Obtain the power consumption requirements parameters of the vehicle.

[0031] Among them, the power consumption requirement parameter is used to indicate the power consumption level of the vehicle in a parked scenario.

[0032] Step S120: Based on the power consumption requirement parameters and the health status of the power supply equipment of each vehicle, predict the target power consumption required by the vehicle in the parking scenario.

[0033] Among them, the health status is used to indicate the state of charge and health of the power supply equipment.

[0034] For example, traditional power supply control often assumes that the power supply capacity is constant, determining the power supply path solely based on the load demand. However, in practical applications, as the vehicle's service life increases or ambient temperature changes, the actual output capacity of power supply equipment (such as low-voltage batteries, DC-DC converters, etc.) will significantly decrease. If decisions are made solely based on power consumption demand parameters, ignoring the power supply's capacity boundaries, it is highly likely that in battery aging or low-temperature environments, the battery may be predicted to be sufficient to support the current load, but in reality, the battery may be unable to provide a stable voltage, leading to system undervoltage reset or functional interruption. This embodiment achieves bidirectional dynamic matching of "demand-capacity" by using health status as a necessary input variable for the prediction model. The state of charge reflects the current remaining energy reserves of the power supply equipment, determining its upper limit of short-term discharge capacity; health reflects the degree of performance degradation of the power supply equipment throughout its entire lifespan, affecting its internal resistance characteristics and long-term load stability. During the prediction process, the power consumption demand parameters are corrected or weighted based on the real-time health status. For example, when the battery's health is detected to be below a preset threshold, even if the current power consumption parameters indicate a light load, the system will automatically increase the estimated margin of the target power consumption or decrease the confidence in the battery's power supply capability, thus favoring the selection of a more reliable external power supply device. This design, which incorporates the power supply's own state into the prediction closed loop, fundamentally solves the problem of decision distortion caused by power supply capability degradation. It ensures that under various extreme operating conditions and throughout the entire lifespan, the predicted target power consumption not only meets functional operation requirements but also remains within the safe operating capabilities of the power supply equipment, significantly improving the system's robustness and safety.

[0035] Step S130: Based on the target power consumption and the output power range supported by each power supply device, control the target power supply device that supports the target output power consumption to supply power to the vehicle.

[0036] The target power consumption falls within the output power range supported by the target power supply equipment.

[0037] For example, after obtaining the target power consumption corrected for health conditions, it is mapped to a predefined output power range for matching. Each power supply device, due to differences in its topology, heat dissipation conditions, and conversion efficiency characteristics, has its most efficient and stable operating range, i.e., its output power range. Only when the load falls within this range can the power supply device operate with optimal energy efficiency and lowest ripple noise. For instance, while a high-power DC-DC converter has extremely high efficiency at rated power, its switching losses increase significantly at very low load rates, causing a sharp drop in conversion efficiency, even below that of a linear regulator; conversely, while a low-power auxiliary power supply has high efficiency under light loads, its overload capacity is limited. This embodiment, through a range matching mechanism, can find the most suitable power supply device for the current operating conditions for the target power consumption. When the target power consumption falls within the output power range of a certain power supply device, that device is prioritized for power supply control; if the target power consumption spans multiple ranges or is at the edge of a range, dynamic selection can be performed using hysteresis control strategies or efficiency optimization algorithms to avoid output voltage fluctuations caused by frequent switching at critical points. Compared to traditional single-point threshold switching, range-based matching control fully considers the physical characteristics of electronic devices, enabling more refined power supply decisions. This not only ensures the stable operation of the parking function but, more importantly, taps into the energy-saving potential of each power supply device under different load conditions, effectively avoiding ineffective losses and preventing overheating risks, thus achieving a dual optimization of energy efficiency and reliability.

[0038] This application's embodiments overcome the inherent defects of static decision-making models in the background art by constructing a complete closed-loop logic of "parameter acquisition - dynamic prediction - interval matching". This solution deeply integrates load demand and power status in the prediction stage, and achieves optimal adaptation of physical characteristics through interval matching in the control stage. It can automatically correct power consumption expectations and select more reliable power supply paths, effectively preventing unexpected power outages or system crashes caused by overestimation of power supply capacity, and significantly improving the accuracy of power supply decisions and the robustness of the system in parking scenarios.

[0039] Regarding step S110, it should be noted that the power consumption demand parameter is not a single-dimensional instantaneous power parameter, but a multidimensional dataset that comprehensively characterizes the energy consumption features of the vehicle's electrical system in a parked state. In a parked scenario, the vehicle's electrical load exhibits significant fluctuations and uncertainties. For example, the intermittent operation of the camera in sentry mode, the compressor's start-stop during remote temperature control, and the peak power consumption of the communication module during big data uploads can all cause drastic changes in actual power consumption within a short period. Therefore, in this embodiment, the power consumption demand parameter includes not only the real-time requested power fed back by each functional controller at the current moment, but also historical average power consumption based on a time window, the nominal power consumption curve of preset functions, and predicted power consumption trends over a future period. By obtaining a set of generalized power consumption demand parameters, a more comprehensive understanding of the current power consumption situation can be achieved, avoiding misjudgments of overall demand due to the sampling time being at a power consumption trough, or over-responding due to instantaneous peaks. For example, when a user activates the remote seat heating function, not only is the current rated power of the heating pad obtained, but also the expected duration and power decay curve of the function under the current operating conditions are obtained in conjunction with the ambient temperature parameter. This multi-dimensional parameter acquisition mechanism lays the data foundation for subsequent accurate predictions, enabling power supply decisions to no longer rely on one-sided instantaneous information.

[0040] Combination Figure 4 The specific method for predicting the target power consumption in step S120 is not limited and can be set according to actual application requirements. For example, in an alternative example, the power consumption requirement parameters include the current required power consumption, historical statistical power consumption, and limit power consumption, and the step of predicting the target power consumption in step S120 can include steps S121 and S122.

[0041] Step S121: Determine the weights of each power consumption requirement parameter based on the health status.

[0042] Step S122: Calculate the target power consumption based on each power consumption requirement parameter and its corresponding weight.

[0043] For example, this embodiment quantifies the abstract prediction process as a multi-dimensional weighted fusion model. The predicted target power consumption... It can be calculated using the following formula 1: =α +β +γ Formula 1; in, It represents the current power consumption demand, which is the sum of the real-time power requests from each functional controller collected at the current moment, reflecting the instantaneous state of the load; Historical statistical power consumption refers to the historical average power consumption value of the same parking function under similar environmental conditions, retrieved from the vehicle database, which reflects the steady-state energy consumption benchmark of the function. This indicates the maximum power consumption, which is the maximum power value or nominal design peak value that the parking function has ever achieved in history, reflecting the upper limit of transient impacts that the load may experience. , , These are the dynamic weighting coefficients for the corresponding parameters, which can be satisfied in an alternative example. It is important to note that these three weighting coefficients are not fixed constants calibrated at the factory, but rather dynamic variables that change in real time depending on the health status of the power supply equipment. The power supply capacity of a power system is a non-linear process that continuously declines over time, due to environmental factors and aging. Therefore, the predictive model must possess adaptive adjustment capabilities to maintain the accuracy of its decisions throughout the vehicle's entire lifecycle.

[0044] Regarding the dynamic adjustment mechanism of the weighting coefficients, this embodiment establishes a mapping relationship between health status and weights. The initial values ​​of the aforementioned weighting coefficients α, β, and γ are obtained based on bench calibration. During actual vehicle operation, the power management module dynamically adjusts the weighting coefficients according to the current SOC, SOH of the 12V lithium battery, and ambient temperature to correct the prediction results and make them closer to the power supply capacity and risks under actual operating conditions. Health status can include dimensions such as state of charge (SOC), state of health (SOH), and ambient temperature. When the battery's SOC is detected to be lower than a preset first threshold (e.g., 30%), or the SOH is lower than a preset second threshold (e.g., 80%), it indicates that the battery's current energy reserves are insufficient or its internal resistance has increased significantly, weakening its ability to withstand instantaneous high-current discharge and increasing the risk of undervoltage protection. At this time, the weighting coefficient corresponding to the limit power consumption is automatically increased. ,make It prioritizes scenarios with potentially high power consumption, thus triggering the second converter to intervene earlier to avoid excessive consumption of the low-voltage battery, while simultaneously reducing the weighting coefficient corresponding to the current power consumption requirement. By increasing the peak weight, the predicted target power consumption is... This tends to favor a conservative, high valuation, making it easier to trigger the second or even the first converter to provide power, thus avoiding over-reliance on the already weakened battery. Conversely, when the battery has a sufficient SOC (e.g., above 70%), good SOH (e.g., above 90%), and the ambient temperature is within a suitable range (e.g., 10°C to 30°C), it indicates that the battery possesses extremely strong independent power supply capability and stability. In this case, the weighting coefficient corresponding to the current power consumption demand is increased. Reduce the weight of historical power consumption statistics and maximum power consumption weight This adjustment allows the prediction results to more sensitively follow actual instantaneous load changes, reduces the frequent wake-up of the DC-DC converter due to overly conservative approaches, maximizes the use of the low-cost energy storage advantages of batteries, and achieves optimal energy efficiency allocation.

[0045] Furthermore, ambient temperature is also a key factor affecting weighting adjustments. When the ambient temperature is extremely low (e.g., below -10°C) or extremely high (e.g., above 40°C), the electrochemical activity of the battery decreases, and both the usable capacity and discharge platform voltage drop significantly. Simultaneously, the power consumption of some low-voltage controllers (such as screens and motors) may increase due to temperature control requirements. Under such extreme conditions, the weighting of historical power consumption is simultaneously increased. and maximum power consumption weight This makes the prediction model more conservative overall, tending to choose a more reliable external power supply path to prevent power instability or unexpected shutdown due to temporary degradation of battery performance.

[0046] It is understood that this embodiment, through a mechanism that drives dynamic changes in weights based on health status, successfully solves the technical challenge of fixed weights failing to balance safety and economy throughout the entire lifecycle, achieving truly adaptive and precise power supply control. It should be understood that the above formula is only a preferred linear weighting implementation. In other embodiments, nonlinear weighting, fuzzy inference, or neural network models can also be used to correct the prediction results based on health status. As long as their essence embodies the idea of ​​dynamically adjusting the prediction tendency according to the power supply state, they should all be covered within the scope of protection of this application.

[0047] Combination Figure 5 The specific method of controlling the power supply of the power supply equipment in step 130 is not limited and can be set according to actual application requirements. For example, in an alternative example, each power supply device includes: a first converter, a second converter, and a battery. It can be understood that the first converter, the second converter, and the battery are all independent power supply devices, and the output power range includes an upper power limit and a lower power limit. The lower power limit of the first converter is greater than or equal to the upper power limit of the second converter, and the lower power limit of the second converter is greater than or equal to the upper power limit of the battery. The step of controlling the power supply of the power supply equipment in step S130 may include steps S131-S133.

[0048] Step S131: When the target power consumption reaches the lower power limit of the first converter, control the power supply of the first converter.

[0049] Step S132: If the target power consumption reaches the lower limit of the power of the second converter but does not reach the upper limit of the power of the second converter, control the power supply of the second converter.

[0050] Step S133: If the target power consumption does not reach the power lower limit of the second converter, control the battery power supply.

[0051] For example, the first converter typically refers to a high-power DC-DC converter connected between the high-voltage power battery and the low-voltage bus, with a relatively large rated power (e.g., 2kW to 3kW), mainly used to meet the needs of high-power loads (such as air conditioning heating and battery heating) during driving or parking. The second converter typically refers to a low-power DC-DC converter integrated inside the high-voltage power battery pack, with a relatively small rated power (e.g., 100W to 200W), designed specifically for low-power parking scenarios (such as sentry mode and remote monitoring), and characterized by high efficiency under light loads. The battery is a traditional 12V low-voltage battery, serving as the system's energy buffer and emergency backup power. The design intention of this three-level architecture is to utilize the efficiency differences of different power supply devices under different load rates to achieve optimal energy efficiency across the entire operating range. It should be understood that although this embodiment uses three power supply devices as examples, in other embodiments, the number of power supply devices can be increased or decreased according to the needs of the vehicle's electrical architecture. For example, a supercapacitor can be added as a fourth-level instantaneous power compensation device, as long as the devices meet the preset power range hierarchy relationship.

[0052] To ensure that power supply equipment at all levels operates within its most efficient operating range and to avoid frequent switching at load critical points, this embodiment strictly hierarchically divides the output power range of each device. For example, the lower power limit of the first converter is greater than or equal to the upper power limit of the second converter, and the lower power limit of the second converter is greater than or equal to the upper power limit of the battery. This hierarchical relationship constructs a non-overlapping and continuously covered power decision space. In this embodiment, the rated power of the second converter (i.e., the low-power DC-DC converter integrated inside the high-voltage power battery pack) is ≤200W, its input is connected to the high-voltage bus, and its output is connected to the low-voltage electrical system. For example, assuming the output power range of the second converter is [10W, 200W], then the lower power limit of the first converter is at least 200W, meaning that the first converter will only be considered for activation when the target power consumption reaches 200W or higher; while the upper power limit of the battery is at most 10W, meaning that the battery will only supply power independently when the target power consumption is below 10W. If a simple single threshold (e.g., 200W) is used for switching, when the actual load fluctuates between 195W and 205W, the system will repeatedly switch between the first and second converters. This not only increases output voltage ripple and affects the lifespan of sensitive electronic components, but also generates additional switching losses due to the frequent soft-start processes of the electronic components. By setting the lower power limit of the first converter to be greater than or equal to the upper power limit of the second converter, a definite decision margin is reserved between the two, ensuring the determinism and stability of the power supply path selection. At the same time, this also ensures that when each power supply stage is selected, its load rate is in the optimal range of its own conversion efficiency curve, avoiding inefficiency losses or overload risks.

[0053] It should be noted that there are two optional implementation methods for determining the boundary between "reached" and "not reached" in this embodiment. In the first implementation method, "reached" means greater than or equal to (≥), and "not reached" means less than (<). For example, when the power limit of the second converter is 200W, "not reaching the power limit of the second converter" means the target power consumption is <200W, and "reaching the power limit of the second converter" means the target power consumption is ≥10W. At this time, the power supply range of the second converter is [10W, 200W]. In the second implementation method, "reached" means greater than (>), and "not reached" means less than or equal to (≤). Taking a power limit of 200W for the second converter as an example, "not reaching the power limit of the second converter" means the target power consumption is ≤200W, and "reaching the power limit of the second converter" means the target power consumption is >10W. In this case, the power supply range of the second converter is (10W, 200W). Both implementation methods can realize the hierarchical control logic of this embodiment. Those skilled in the art can flexibly choose according to the specific system accuracy requirements, sensor resolution, and hysteresis control strategy. Regardless of which method is used, as long as the hierarchical relationship of the power supply ranges of each power supply device remains unchanged, it falls within the protection scope of this application.

[0054] Based on the aforementioned power range definition, this embodiment provides a specific hierarchical control strategy. When the target power consumption reaches the lower power limit of the first converter, the first converter is controlled to supply power. This corresponds to high-power parking scenarios, such as when a user activates the remote cabin heating function in winter, in which case the target power consumption may be as high as 1500W, far exceeding the capacity of the second converter. Upon recognizing this demand, the three-electric system is activated, the high-voltage relay is closed, and the first converter is connected to the high-voltage bus to supply power to the low-voltage load. In this mode, although the light-load efficiency of the first converter is low, the overall conversion efficiency remains at a high level because the current load is close to its rated power point, and the normal operation of high-power functions can be guaranteed.

[0055] When the target power consumption reaches the lower limit of the second converter's power but not the upper limit, the second converter is powered. This is the core energy-saving optimization range of this embodiment, covering most common parking functions such as sentry mode, data upload, and remote diagnostics. In this scenario, the target power consumption is typically between 20W and 180W, falling precisely within the high-efficiency operating range of the second converter. Compared to traditional solutions that require waking up the entire high-voltage system and the first converter to handle this small load, this embodiment, by activating the second converter integrated within the battery pack, not only avoids the no-load loss of the first converter itself (typically 10W-30W) but also eliminates the static power consumption generated by high-voltage components such as the vehicle controller and motor controller to maintain standby, significantly extending the vehicle's pure electric parking range. It is important to note that a strict safety interlock check must be performed before powering the second converter. Since the input terminal of the second converter is directly connected to both ends of the high-voltage power battery cell, if the high-voltage relay is closed at this time, the first and second converters may operate simultaneously, leading to circulating current or voltage conflict. Therefore, before issuing the enable command for the second converter, the control module first reads the status feedback signal of the high-voltage relay. If the relay is not disconnected, the second converter is forcibly prevented from starting, and the power supply to the first converter is maintained or a safety protection mode is entered first. Only after confirming that the high-voltage relay has reliably disconnected is the second converter activated via a hard-wired wake-up signal from the BMS. The BMS controls the start and stop of the second converter through hard-wired signals and performs fault diagnosis and data logging. This detection-before-control timing logic is a key safeguard for ensuring the safe and reliable operation of the dual DC-DC architecture.

[0056] When the target power consumption does not reach the lower power limit of the second converter, the battery is used for power supply. This corresponds to extremely low-power deep sleep scenarios, such as when the vehicle is parked for a long time and no active functions are triggered, with only microampere or milliampere loads such as the anti-theft alarm and T-BOX heartbeat device operating. In this case, even the highly efficient second converter may have its own control circuit power consumption exceed that of the load itself, resulting in energy waste. Therefore, all DC-DC converters are completely shut down, and the low-voltage battery directly powers these basic loads. The low-voltage battery here is specifically a 12V lithium battery. Compared with traditional lead-acid batteries, 12V lithium batteries have advantages such as high energy density, long cycle life, and low self-discharge rate, making them more suitable as an energy buffer in parked scenarios. This design enables the system to achieve true zero conversion loss under extremely light load conditions, minimizing the risk of battery depletion caused by long-term parking. Of course, to prevent the battery from being over-discharged, a minimum SOC threshold or a maximum duration limit is usually set. Once this boundary is reached, even if the target power consumption is still lower than the power limit of the second converter, the second converter will be periodically woken up to replenish the battery, thus forming a dynamic balance.

[0057] In addition to the normal hierarchical power supply logic, this embodiment also incorporates a robust fault-tolerance mechanism to address the extreme scenario of second converter failure. As an optional implementation, in the event of a second converter failure, power is switched to the first converter. For example, when the control module or BMS detects a fault in the second converter such as over-temperature, over-voltage, short circuit, or communication loss, a degraded power supply strategy is immediately triggered. First, the BMS quickly shuts down the second converter via a hard-wired signal to prevent the fault from escalating, and simultaneously records the fault code to non-volatile memory. Then, the power management module determines whether high-voltage power is required: if high voltage is not required (i.e., the current target power consumption can be handled independently by the battery), the BMS enters a sleep state, with the battery maintaining the basic load; if high voltage is required (i.e., the current target power consumption exceeds the battery's safe discharge capacity, or the expected duration is long), the three-electric system is automatically woken up and the high-voltage relay is closed, seamlessly switching to the first converter to take over the power supply task. This redundant design ensures that even if the auxiliary power supply fails, the vehicle's core parking functions can still maintain basic operation, greatly improving system robustness and user experience. It should be understood that the triggering conditions for fault switching are not limited to hardware failures of the second converter itself. They may also include systemic abnormal states such as low ambient temperature causing the second converter to operate at a reduced rate and fail to meet the demand, or low battery SOC requiring urgent high-current charging. As long as it is determined that the second converter cannot continue to perform the current power supply task, it can be included in the switching logic scope of this embodiment.

[0058] Therefore, this embodiment constructs a tiered power range matching mechanism for three-level power supply equipment, translating the abstract range matching strategy into concrete hardware execution logic. This mechanism not only achieves efficient coverage of the entire power range at the physical level, but also solves the challenges of energy efficiency optimization and conflict protection in multi-power parallel systems at the control level through strict boundary definitions and safe interlocking timing. Combined with the automatic degradation switching capability under fault conditions, it forms a parking power supply control system that is energy-saving, environmentally friendly, safe, and reliable.

[0059] This application further constructs a feedback adjustment mechanism based on actual operating data, upgrading the unidirectional power consumption prediction into a closed-loop control system with self-evolution capabilities. As an optional implementation, the method also includes: monitoring the vehicle's actual power consumption, and switching to a power supply device with a higher output power range when the actual power consumption is greater than or equal to the output power range of the target power supply device.

[0060] For example, although the prediction model has comprehensively considered multi-dimensional parameters and health status, due to the random fluctuations of parking load, sensor sampling noise, and the simplification assumptions of the model itself, there will inevitably be a deviation between the predicted target power consumption and the actual power consumption. If a one-time decision is made based solely on the prediction results without runtime monitoring, when the actual load experiences unexpected spikes or continuous increases, the currently selected power supply equipment may trigger protection shutdown due to overload, leading to a power outage. Therefore, this embodiment introduces real-time power consumption monitoring as a safety net and dynamic correction layer for prediction decisions. During execution, the power management module continuously acquires the vehicle's actual power consumption at a preset high-frequency sampling rate (e.g., 10ms to 100ms) through current sensors and voltage sampling circuits on the low-voltage bus. To avoid erroneous switching due to transient interference signals, the sampled data is typically processed by moving average filtering or median filtering to extract effective values ​​that reflect the true load trend. When the system detects that the effective value is greater than or equal to the upper limit of the output power range of the currently operating power supply equipment, or although it has not exceeded the upper limit but has been continuously in the high load warning zone (e.g., reaching more than 90% of the upper limit) for a preset time, it immediately determines that the current power supply equipment cannot meet the demand and triggers a switching process to a higher-level power supply equipment. For example, when the second converter is supplying power to the sentry mode, if the user suddenly remotely turns on the seat heating function, causing the actual power consumption to surge from 80W to 250W, exceeding the 200W power limit of the second converter, the system will quickly wake up the first converter to take over the power supply. This rapid response mechanism based on measured values ​​ensures that even if the predictive model fails to accurately predict extreme operating conditions, the power supply continuity can still be maintained through real-time feedback at the physical level, effectively preventing voltage drops or device damage caused by overload, and significantly improving the robustness and safety of the system. It should be understood that the “switching” here includes not only upgrading from low-power devices to high-power devices, but also, in some implementations, redundant switching between devices at the same level, or downgrading to lower-power devices after the measured power consumption is much lower than expected and has been stable for a period of time, so as to achieve secondary energy efficiency optimization during operation.

[0061] Building upon this, to further improve the accuracy of the prediction model throughout its entire lifecycle, this embodiment also introduces an online learning and adaptive update mechanism for the weight parameters. As an optional implementation, the method further includes updating the weights corresponding to each power consumption requirement parameter based on the actual power consumption.

[0062] For example, this feature transforms the power supply control system from a static execution unit into an intelligent agent with learning capabilities. During actual vehicle use, as components age, environmental climate changes, and user habits solidify, the initially calibrated weighting coefficients may gradually deviate from their optimal values. For instance, a vehicle frequently used in cold regions may exhibit significantly different actual power consumption characteristics at low temperatures compared to its factory-calibrated data at room temperature; or, with increasing usage years, the internal impedance of some controllers may increase, leading to a rise in base power consumption. If the weighting coefficients remain constant, the error in the prediction model will accumulate and amplify. This embodiment addresses this problem by establishing a closed-loop feedback chain of "prediction-measurement-correction." After each parking function operation, or at periodic system inspection nodes, the deviation between the actual power consumption and the predicted target power consumption within the current operating cycle is calculated. Regarding the periodic inspection mechanism, the BMS wakes up every 4 hours to check the status of the second converter and battery parameters (including SOC, SOH, temperature, etc.). Simultaneously, the power management module stores the actual power consumption data from the current parking function as new historical data in the database. This data is used to periodically retrain or update the weight coefficients of the power consumption prediction algorithm, continuously optimizing the prediction model. If the deviation value remains positive (i.e., actual power consumption is consistently higher than the predicted value), it indicates that the current prediction strategy is too optimistic and underestimates the load demand. In this case, the weight allocation is automatically adjusted, for example, appropriately increasing the weight of the extreme power consumption γ or the historical statistical power consumption weight β, while decreasing the weight of the current demand power consumption α, making the prediction results more conservative and safer in similar scenarios in the future. Conversely, if the deviation value remains negative (i.e., actual power consumption is consistently lower than the predicted value), it indicates that the prediction strategy is too conservative, causing unnecessary energy waste (such as frequent wake-ups of high-power converters). In this case, the system will adjust the weights in reverse, increasing the confidence in instantaneous low-power states, thereby exploring more energy-saving potential.

[0063] Regarding the specific execution logic of weight updates, two methods can be adopted: incremental updates or batch retraining. In incremental updates, the Exponentially Weighted Moving Average (EWMA) algorithm is used to gradually integrate newly generated deviation information into the existing weights with a small learning rate. This method has low computational cost, is suitable for real-time execution by automotive embedded processors, and can smoothly transition to avoid parameter abrupt changes. In batch retraining, historical power consumption data accumulated over a period of time (such as one week or one month) is stored in non-volatile memory. When the vehicle is in deep sleep or during charging idle periods, a background optimization algorithm is invoked to globally optimize the weight coefficients. Regardless of the method used, the updated weight parameters are persistently saved, ensuring that the vehicle can inherit the latest decisions the next time it is powered on. Through this adaptive update mechanism, the power supply control system of this application can automatically adapt to the unique aging curve of each vehicle and the personalized power consumption habits of each owner. Compared to existing technologies that rely on fixed parameters or offline calibration, this embodiment not only solves the energy consumption optimization problem in the case of a new vehicle, but also ensures that the vehicle maintains the optimal balance between energy efficiency and reliability throughout its service life of several years or even more than ten years, greatly extending the service life of the vehicle's electrical system and improving the user experience.

[0064] To more clearly illustrate the technical advantages of the above-mentioned solutions in this application, the embodiments of this application will provide a detailed description of the implementation scheme of this application using typical application scenarios.

[0065] For example, combined Figure 6 In order to integrate the scattered technical features in the aforementioned embodiments into a complete and executable control flow, this embodiment combines... Figure 6 The flowchart shown illustrates the integrated DC-DC control strategy within the battery pack, providing a sequential explanation of the entire process from the vehicle entering parking mode to the system's final hibernation.

[0066] like Figure 6 As shown, the entire control process is triggered by one or more parking functions activated by the user after the vehicle is in the OFF position. When a function controller (such as a sentry mode controller, remote diagnostic module, etc.) is activated, the power management module is woken up and enters the "function triggering and data preparation" stage. In this stage, the power management module collects the power consumption requests of all function controllers that need to be woken up this time through the vehicle bus, and retrieves the historical statistical power consumption and extreme power consumption data of the corresponding functions under similar environmental conditions from the internal historical database to complete the acquisition of power consumption requirement parameters.

[0067] The process then proceeds to the "Power Consumption Statistics and Prediction" stage. The power consumption prediction algorithm unit in the power management module integrates three parameters: current power demand, historical power consumption, and extreme power consumption. It also combines the state of charge and health of the low-voltage battery fed back by the BMS module to calculate the target power consumption prediction value according to the weighted prediction model.

[0068] After the prediction is completed, the process enters the core "power supply path decision" branch. The power management module compares the predicted target power consumption with a preset power threshold, and based on the comparison result, selects one of three mutually exclusive power supply paths: First path: If the predicted target power consumption reaches the lower power limit of the first converter (high-power DC-DC converter) (e.g., ≥200W), it indicates that the current power consumption demand exceeds the carrying capacity of the second converter (low-power DC-DC converter). At this time, the power management module sends a wake-up request for the three-electric system to the vehicle controller. After the high-voltage relay closes, the first converter draws power from the high-voltage power battery and supplies power to the various functional controllers on the low-voltage bus.

[0069] The second path: If the predicted target power consumption reaches the lower limit of the second converter's power but not the upper limit (e.g., the range of 10W to 200W), it indicates that the second converter can efficiently cover the current load. In this case, the process does not directly start the second converter, but first enters the safety interlocking step of "checking the high-voltage relay status." The BMS module reads the status feedback signal of the high-voltage relay: if it detects that the relay is not disconnected, it forcibly prevents the second converter from starting, maintaining power supply to the first converter or entering a safety protection mode to prevent circulating current or voltage conflicts caused by simultaneous operation of the first and second converters; only after confirming that the high-voltage relay has reliably disconnected does the BMS module activate the second converter via a hard-wired wake-up signal, enabling it to start supplying power to the low-voltage system.

[0070] After the second converter starts up, the process enters the "Dynamic Monitoring of Second Converter Status and Power Consumption" stage. The BMS module continuously diagnoses whether the second converter has malfunctioned. If the second converter is operating normally, the three-electric system remains in deep sleep mode, with the second converter solely supplying power to the low-voltage load to achieve maximum energy savings. At the same time, the power management module continuously monitors the actual power consumption. When the actual power consumption approaches or exceeds the power limit of the second converter, it performs operations such as dynamic adjustment, early warning, or switching to the first converter.

[0071] If the BMS module diagnoses a fault in the second converter (such as over-temperature, over-voltage, short circuit, or communication loss), it triggers a fault handling sub-process: the second converter wakes up the BMS module via a hard-wired signal, the BMS module then wakes up the power management module and records the fault code to non-volatile memory, and then shuts down the second converter via a hard-wired signal to prevent the fault from escalating. Afterwards, the power management module determines whether high voltage is needed based on current functional requirements and battery status: if the current load can be handled independently by the low-voltage battery, the BMS module re-enters sleep mode; if high voltage power is required, it wakes up the three-electric system and closes the high-voltage relay, seamlessly switching power supply to the first converter.

[0072] The third path: If the predicted target power consumption does not reach the lower power limit of the second converter (e.g., <10W), it indicates that the current power consumption is extremely low, and only microampere or milliampere loads such as burglar alarms and T-BOX heartbeat devices are working. In this case, the system chooses to completely shut down all DC-DC converters, and the low-voltage battery directly powers these basic loads. The three-electric system and BMS module all enter a deep sleep state, achieving extreme energy saving with zero conversion loss.

[0073] Regardless of which power supply path is selected, the process ultimately converges on the "periodic inspection and model update" stage during system operation or after entering hibernation. During hibernation, the BMS module wakes up every preset period (e.g., 4 hours) to check the status of the second converter and battery parameters (including state of charge, health, temperature, etc.). Simultaneously, the power management module stores the actual power consumption curve recorded during this parking function operation cycle as new training data in the historical database. This data is used to optimize the weight coefficients in the power consumption prediction algorithm or retrain the machine learning model during the vehicle's next power-on or periodic maintenance. The specific implementation of this adaptive update mechanism has been detailed in Example 4.

[0074] Through the aforementioned complete control flow, this application constructs a full-link closed-loop control system encompassing "function triggering → power consumption prediction → path decision → safety interlocking → dynamic monitoring → fault tolerance → periodic inspection → model evolution." Figure 6 As shown, the branches are organically connected through clear judgment conditions and signal interaction links, which not only ensures optimal energy efficiency under normal operating conditions, but also covers safety nets for abnormal operating conditions such as faults, overloads, and extreme environments. At the same time, the system's decision-making capabilities are continuously evolved through periodic model updates.

[0075] Furthermore, this embodiment provides a multi-scenario integrated application example, which verifies the feasibility and beneficial effects of the vehicle power supply control method by demonstrating the operation of typical functions when the vehicle is parked.

[0076] Taking Sentry Mode as an example, assuming the vehicle is operating at a normal ambient temperature of 25℃, the low-voltage battery's SOC is 80% and SOH is 95%. After the user locks the vehicle and activates Sentry Mode, the power management module obtains the current power consumption demand as 60W, the historical power consumption as 70W, and the maximum power consumption as 120W. Since the battery health is good, weights are set as α=0.6, β=0.3, and γ=0.1, calculating a target power consumption prediction of 69W. This value falls within the output power range of the second converter [10W, 200W]. After confirming the high-voltage relay is disconnected, the control module wakes up the second converter via a hardwired connection to supply power independently, while the first converter and the three-electric system remain in deep sleep mode. Actual testing shows that under the same Sentry Mode operation for 8 hours, this solution consumes approximately 0.48kWh of high-voltage battery power, while the traditional solution using the first converter consumes approximately 0.72kWh, resulting in an energy saving rate of 33.3%.

[0077] Taking remote seat heating and steering wheel heating as examples again. The seat heating pad has a rated power of 100W, and the steering wheel heating module has 50W, with a current total power consumption requirement of 150W. Combining historical power consumption of 130W and the maximum power consumption of 180W, and setting weights α=0.5, β=0.3, and γ=0.2, the calculated target power consumption prediction value is 150W. This value falls within the output power range of the second converter, which supplies power to the system independently. The entire electric system remains in deep sleep mode, avoiding unnecessary energy consumption caused by waking up the entire electric system.

[0078] Furthermore, the technical solution of this application is also applicable to the following parking power supply scenarios: (1) Big data upload after vehicle voltage drops: Only T-BOX and gateway need to work, power consumption is about 15W, and the battery independently supplies power to achieve zero conversion loss; when the instantaneous power consumption suddenly increases to 25W, the system automatically switches to the second converter.

[0079] (2) Remote light show welcome: The main loads include the vehicle body ambient light, the headlight dynamic effect control module and the audio playback module, with a total power consumption of 50W to 120W. It is powered by the second converter to avoid deep discharge of the low-voltage battery.

[0080] (3) Vehicle rest: Typical loads include seat electric adjustment motor, ambient light, white noise playback module and air conditioning low wind mode, with a total power consumption of about 80W to 150W, powered by the second converter.

[0081] (4) Remote diagnostics: Multiple domain controllers need to be woken up to enter diagnostic mode. The power consumption fluctuates from 30W standby to 120W peak, and is powered by the second converter.

[0082] (5) The second converter maintains uniform heating of the water pump when the battery thermal runaway occurs: After the high voltage relay is disconnected, the second converter integrated inside the battery pack can continue to draw power from the high voltage cell to provide continuous power to the water pump and prolong the uniform heating time.

[0083] (6) The second converter avoids low-voltage battery depletion in the OFF position: The second converter can work in the OFF position and dynamically decides whether to take over the power supply or replenish the battery according to the battery SOC status.

[0084] (7) The second converter supplies power to the BMS in the battery swapping mode: When the vehicle is powered off, the second converter integrated inside the battery pack draws power directly from the high-voltage cell to provide independent working power to the BMS.

[0085] The above embodiments describe in detail the vehicle power supply control method provided in this application. In other embodiments, this application also provides a vehicle power supply control device. Figure 7 This is a block diagram illustrating vehicle power supply control according to an embodiment of this application, such as... Figure 7 As shown, the vehicle power supply control 300 includes: an acquisition module 310, a prediction module 320, and a control module 330.

[0086] The acquisition module 310 is used to acquire the power consumption requirement parameters of the vehicle. The power consumption requirement parameters are used to indicate the power consumption level of the vehicle in a parked scenario.

[0087] The prediction module 320 is used to predict the target power consumption required by the vehicle in a parking scenario based on power consumption requirement parameters and the health status of the power supply equipment in each vehicle. The health status is used to indicate the state of charge and health of the power supply equipment.

[0088] The control module 330 is used to control a target power supply device that supports the target power consumption to supply power to the vehicle based on the target power consumption and the output power range supported by each power supply device. The target power consumption falls within the output power range supported by the target power supply device.

[0089] In other embodiments, this solution also provides an in-vehicle device, such as... Figure 8 As shown, the vehicle-mounted device 400 also includes a processor 410 and one or more memories 420. The one or more memories 420 are used to store program instructions executed by the processor 410. When the processor 410 executes the program instructions, it implements the vehicle power supply control method described above.

[0090] Furthermore, the processor 410 may include one or more processing cores. The processor 410 runs or executes instructions, programs, code sets, or instruction sets stored in the memory 420, and retrieves data stored in the memory 420. Optionally, the processor 410 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 410 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor and may be implemented using a separate communication chip.

[0091] In other embodiments, this solution also provides a vehicle. Figure 9 This is a block diagram of a vehicle according to an embodiment of this application, such as... Figure 9 As shown, the vehicle 500 includes: a body 510, multiple power supply devices 520 and the aforementioned on-board equipment 400.

[0092] Each power supply device 520 is installed inside the vehicle body 510, and the vehicle-mounted equipment 400 is connected to each power supply device 520.

[0093] In other embodiments, this solution also provides a computer-readable storage medium, which may be included in the cloud server described in the above embodiments; or it may exist independently and not assembled into the cloud server. The aforementioned computer-readable storage medium carries computer-readable instructions, which, when executed by a processor, implement the methods in any of the above embodiments.

[0094] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. Computer-readable storage media can be, for example, but not limited to: electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0095] In an exemplary embodiment, this application also provides a computer program product, which, when executed by a processor, is used to implement the above-described vehicle power supply control method.

[0096] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0097] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0098] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A vehicle power supply control method, characterized in that, The method includes: Obtain the power consumption requirement parameters of the vehicle; the power consumption requirement parameters are used to indicate the power consumption level of the vehicle in a parking scenario; Based on the power consumption requirement parameters and the health status of the power supply equipment of each vehicle, the target power consumption required by the vehicle in the parking scenario is predicted; the health status is used to indicate the state of charge and health of the power supply equipment. Based on the target power consumption and the output power range supported by each of the power supply devices, the target power supply device that supports outputting the target power consumption is controlled to supply power to the vehicle; the target power consumption belongs to the output power range supported by the target power supply device.

2. The method according to claim 1, characterized in that, Each of the power supply devices includes: a first converter, a second converter, and a battery; the output power range includes an upper power limit and a lower power limit, the lower power limit of the first converter is greater than or equal to the upper power limit of the second converter, and the lower power limit of the second converter is greater than or equal to the upper power limit of the battery; the step of controlling the target power supply device that supports outputting the target power consumption to supply power to the vehicle according to the target power consumption and the output power range supported by each of the power supply devices includes: When the target power consumption reaches the lower power limit of the first converter, the power supply of the first converter is controlled. If the target power consumption reaches the lower power limit of the second converter but does not reach the upper power limit of the second converter, control the power supply of the second converter. If the target power consumption does not reach the lower power limit of the second converter, the battery is controlled to supply power.

3. The method according to claim 2, characterized in that, The method further includes: In the event of a failure of the second converter, power is switched to the first converter.

4. The method according to claim 1, characterized in that, The power consumption requirement parameters include current power consumption requirement, historical statistical power consumption, and maximum power consumption. The step of predicting the target power consumption required by the vehicle in the parking scenario based on the power consumption requirement parameters and the health status of the power supply equipment of each vehicle includes: The weights corresponding to each of the power consumption requirement parameters are determined based on the health status. The target power consumption is calculated based on the power consumption requirement parameters and their corresponding weights.

5. The method according to claim 4, characterized in that, The method further includes: Monitor the actual power consumption of the vehicle, and if the actual power consumption is greater than or equal to the output power range of the target power supply device, switch to a power supply device with a higher output power range for power supply.

6. The method according to claim 5, characterized in that, The method further includes: The weights corresponding to each power consumption requirement parameter are updated based on the actual power consumption.

7. A vehicle power supply control device, characterized in that, The device includes: The acquisition module is used to acquire the power consumption requirement parameters of the vehicle; the power consumption requirement parameters are used to indicate the power consumption level of the vehicle in a parking scenario. The prediction module is used to predict the target power consumption required by the vehicle in the parking scenario based on the power consumption requirement parameters and the health status of the power supply equipment of each vehicle; the health status is used to indicate the state of charge and health of the power supply equipment. The control module is used to control the target power supply device that supports outputting the target power consumption to supply power to the vehicle based on the target power consumption and the output power range supported by each of the power supply devices; the target power consumption belongs to the output power range supported by the target power supply device.

8. A vehicle-mounted device, characterized in that, The vehicle-mounted equipment includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 6.

9. A vehicle, characterized in that, include: The vehicle body, multiple power supply devices, and the vehicle-mounted device as claimed in claim 8; each of the power supply devices is disposed inside the vehicle body, and the vehicle-mounted device is connected to each of the power supply devices.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1 to 6.

11. A computer program product, characterized in that, The computer program product includes computer instructions, which are stored in a computer-readable storage medium. The computer instructions are read and executed by the processor of the computer device to implement the method as described in any one of claims 1 to 6.

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