Vehicle energy management method and system

Abstract

The present disclosure provides a vehicle energy management method and system, relating to the technical field of vehicle control. The method comprises: in response to a low-voltage switching signal, switching a target vehicle to a low-voltage power supply mode; obtaining first state data of the target vehicle, the first state data comprising a low-voltage load power, a battery state of a low-voltage system, and an ambient temperature; based on the first state data, predicting a sustainable time of the low-voltage system; based on the sustainable time, a voltage drop rate of the low-voltage system, and user usage habit information, determining a target control scheme, the target control scheme being used to control whether the high-voltage system charges the low-voltage system, thereby improving the energy efficiency of the high-voltage system and optimizing vehicle energy management.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle control technology, specifically to vehicle energy management methods and systems. Background Technology

[0002] New energy vehicles are typically equipped with two independent electrical systems: a high-voltage system and a low-voltage system. When the vehicle is stationary, if the low-voltage system's power is insufficient, the high-voltage system needs to charge it to maintain the stable operation of the low-voltage system.

[0003] Therefore, optimizing the energy management strategy for new energy vehicles has become crucial for improving vehicle range, reliability, and user experience. Currently, low-voltage battery charging strategies typically employ fixed thresholds or timed triggering methods, which cannot adapt to battery aging, changes in ambient temperature, and diverse user habits, easily leading to suboptimal charging timing. Summary of the Invention

[0004] In view of this, embodiments of the present disclosure provide a vehicle energy management method and system to solve the problem that the low flexibility of the charging strategy leads to low accuracy in controlling the charging timing.

[0005] In a first aspect, one embodiment of this disclosure provides a vehicle energy management method applied to a target vehicle, the target vehicle including a high-voltage system and a low-voltage system. The method includes: switching the target vehicle to a low-voltage power supply mode in response to a low-voltage switching signal; acquiring first state data of the target vehicle, the first state data including low-voltage load power, battery state of the low-voltage system, and ambient temperature; predicting the duration of the low-voltage system based on the first state data; and determining a target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage habit information, the target control scheme being used to control whether the high-voltage system charges the low-voltage system.

[0006] The aforementioned vehicle energy management method, based on the acquired first-state data, dynamically decides the charging timing of the high-voltage system by combining the voltage drop rate and user habit information, thereby adaptively optimizing the energy management process. It effectively solves the problems of high static energy consumption, poor charging timing (risk of premature wake-up or power depletion) and low overall energy efficiency caused by passive response strategies, reduces unnecessary energy consumption, and ensures continuous and reliable power supply to the low-voltage system.

[0007] In conjunction with the first aspect, in some implementations of the first aspect, a target control scheme is determined based on the duration, the voltage drop rate of the low-voltage system, and user usage habit information, including: determining the duration of the charging reference cycle based on user usage habit information; quantifying the duration into the equivalent remaining energy cycle number in units of the charging reference cycle based on the duration of the charging reference cycle; and generating the target control scheme based on the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system.

[0008] The aforementioned vehicle energy management method converts user usage habit information into a charging baseline cycle duration and quantifies the available duration into an equivalent number of remaining energy cycles. This enables energy prediction to more accurately match the user's actual vehicle usage pattern, thereby solving the problem of charging timing deviation caused by the mismatch between the charging baseline cycle and user habits. It also avoids the risk of frequently waking up the high-voltage system or running out of power, further improving energy consumption optimization efficiency.

[0009] In conjunction with the first aspect, in some implementations of the first aspect, a target control scheme is generated based on the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system, including: generating the target control scheme based on at least one preset rule from a preset rule set, using the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system as conditions.

[0010] The aforementioned vehicle energy management method introduces a rule base to make conditional decisions based on the equivalent remaining energy cycle number, user usage habits, and voltage drop rate, thereby generating a target control scheme. This achieves a rule-driven, systematic control logic and enhances flexibility.

[0011] In conjunction with the first aspect, in some implementations of the first aspect, the preset rule set includes a fuzzy rule base. Based on at least one preset rule in the preset rule set, and using the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate of the low-voltage system as conditions, a target control scheme is generated, including: mapping the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate to corresponding fuzzy semantic levels; inputting the fuzzy semantic levels corresponding to the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate into the fuzzy rule base for inference to obtain the target control scheme.

[0012] The aforementioned vehicle energy management method effectively handles uncertainties such as battery state fluctuations by mapping the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate to fuzzy semantic levels, and generating control schemes based on fuzzy rule base reasoning. This improves the decision-making adaptability and robustness in dynamic environments.

[0013] In conjunction with the first aspect, in some implementations of the first aspect, the preset rule set includes at least one of the following preset rules: if the equivalent remaining energy cycle number is less than a first threshold and the voltage drop rate is greater than a second threshold, then a target instruction indicating immediate charging is generated; if the user's habitual information indicates that the target vehicle is about to enter a long-term parking mode and the equivalent remaining energy cycle number is greater than a third threshold, then a target trigger threshold indicating a first charging cycle is generated; if the voltage drop rate is less than a fourth threshold, then a target trigger threshold indicating a second charging cycle is generated, wherein the duration of the first charging cycle is greater than the duration of the second charging cycle.

[0014] The aforementioned vehicle energy management method defines the specific rules of the fuzzy rule base, optimizes the charging triggering conditions, solves the problem of unnecessary wake-ups, improves response efficiency, and achieves energy efficiency balance.

[0015] In conjunction with the first aspect, in some implementations of the first aspect, the duration of the charging reference cycle is determined based on user usage habit information, including: determining the expected parking time or expected usage frequency of the target vehicle based on user usage habit information; and determining the duration of the charging reference cycle based on the expected parking time or expected usage frequency with the goal of maintaining the low-voltage system's charge level not lower than a preset health threshold.

[0016] The vehicle energy management method described above determines the expected parking time by combining user habit information and sets a charging reference cycle with the goal of maintaining low-voltage power above the health threshold. This ensures battery health while adapting to user habits, effectively preventing over-discharge of the battery and extending battery life.

[0017] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: controlling the high-voltage system to charge the low-voltage system based on a target control scheme; wherein, controlling the high-voltage system to charge the low-voltage system based on the target control scheme includes: counting the cumulative number of cycles experienced by the low-voltage system since the last charging using a counter; controlling the high-voltage system to charge the low-voltage system when the cumulative number of cycles is greater than or equal to a charging trigger threshold; and controlling the high-voltage system to charge the low-voltage system when the voltage of the low-voltage system is less than a voltage threshold.

[0018] The aforementioned vehicle energy management method, by accumulating the number of cycles using a counter, sets a dual trigger path with charging trigger threshold and voltage threshold, ensuring reliable execution of charging commands, reducing the risk of missed or false triggers, and enhancing the operability and system stability of the control scheme.

[0019] In conjunction with the first aspect, in some implementations of the first aspect, the battery state of the low-voltage system includes the remaining battery capacity and battery health of the low-voltage system; based on the first state data, predicting the duration of the low-voltage system includes: calculating the effective available power of the low-voltage system based on the remaining battery capacity, battery health, and ambient temperature; and determining the duration of the low-voltage system based on the effective available power and the low-voltage load power.

[0020] The vehicle energy management method described above calculates the effective available power by incorporating battery health and ambient temperature, rather than relying solely on the remaining power, thus more accurately predicting the duration of operation. This solves the prediction bias problem caused by battery aging or temperature fluctuations and optimizes the accuracy of energy management.

[0021] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: switching the target vehicle to a high-voltage power supply mode in response to a high-voltage switching signal; acquiring second state data of the target vehicle, the second state data including the remaining battery power of the high-voltage system; and dynamically adjusting the power output weight of the high-voltage system between the drive system and the body accessory system of the target vehicle based on the remaining battery power of the high-voltage system.

[0022] The aforementioned vehicle energy management method dynamically adjusts the power output weights of the drive system and the vehicle accessory system based on the high-voltage battery charge in high-voltage mode, achieving a real-time balance between power, comfort, and range. This solves the energy distribution conflict problem in the high-voltage system and improves energy efficiency.

[0023] Secondly, one embodiment of this disclosure provides a vehicle energy management device, the device comprising: a switching module configured to switch a target vehicle to a low-voltage power supply mode in response to a low-voltage switching signal; an acquisition module configured to acquire first state data of the target vehicle, the first state data including low-voltage load power, battery state of the low-voltage system, and ambient temperature; a prediction module configured to predict the duration of the low-voltage system based on the first state data; and a control module configured to determine a target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage habit information, the target control scheme being used to control whether the high-voltage system charges the low-voltage system.

[0024] Thirdly, one embodiment of this disclosure provides a vehicle energy management system, including: a relay for switching between a low-voltage power supply mode and a high-voltage power supply mode; a current sensor for collecting the current of the high-voltage system and the low-voltage system; and a processor for executing the vehicle energy management method of the first aspect.

[0025] Fourthly, one embodiment of this disclosure provides a computer-readable storage medium storing a computer program for performing the vehicle energy management method of the first aspect. Attached Figure Description

[0026] The above and other objects, features, and advantages of this disclosure will become more apparent from the more detailed description of the embodiments thereof in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the disclosure and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0027] Figure 1 The diagram shown is a schematic flowchart of a vehicle energy management method provided in an embodiment of this disclosure.

[0028] Figure 2 The diagram shown is a flowchart illustrating the steps for determining a target control scheme based on the duration of operation, the voltage drop rate of the low-voltage system, and user usage habits, according to an embodiment of this disclosure.

[0029] Figure 3 The diagram shown is a flowchart of a vehicle energy management method provided in another embodiment of this disclosure.

[0030] Figure 4 The diagram shown is a flowchart of a vehicle energy management method provided in another embodiment of this disclosure.

[0031] Figure 5 The diagram shown is a structural schematic of a vehicle energy management device provided in an embodiment of this disclosure.

[0032] Figure 6 The diagram shown is a structural schematic of a vehicle energy management system provided in an embodiment of this disclosure. Detailed Implementation

[0033] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0034] For new energy vehicles, in order to optimize energy management strategies, related technologies generally control the charging of the low-voltage battery by the high-voltage battery through a fixed voltage threshold or a timed triggering mechanism, which is a passive response approach. Specifically, when the low-voltage battery voltage is lower than a preset threshold or reaches a fixed time interval, the high-voltage battery is activated to charge the low-voltage battery, thus achieving charging.

[0035] However, when the vehicle is stationary (e.g., parked), the above-mentioned fixed voltage threshold scheme will frequently wake up the high voltage system, resulting in increased static energy consumption; and the fixed time interval scheme will cause the charging timing to be unable to adapt to the user's usage habits (e.g., short-distance high-frequency use, long-term parking, etc.).

[0036] To address the above issues, this disclosure provides a vehicle energy management method and system. The vehicle energy management method is applied to a target vehicle, which includes a high-voltage system and a low-voltage system. The method includes: switching the target vehicle to a low-voltage power supply mode in response to a low-voltage switching signal; acquiring first state data of the target vehicle, including low-voltage load power, battery status of the low-voltage system, and ambient temperature; predicting the duration of the low-voltage system based on the first state data; and determining a target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage habits. The target control scheme controls whether the high-voltage system charges the low-voltage system and can calculate the working time of the low-voltage battery under current conditions based on user habits and battery health. This achieves adaptive control, optimizes energy management, reduces static energy consumption, and improves energy efficiency.

[0037] Figure 1 The diagram shown is a schematic flowchart of a vehicle energy management method according to an embodiment of this disclosure. Figure 1 As shown in the embodiments of this disclosure, the vehicle energy management method includes the following steps.

[0038] Step S110: In response to the low-voltage switching signal, the target vehicle is switched to low-voltage power supply mode.

[0039] A low-voltage switching signal can be a signal used to trigger a target vehicle to switch from a high-voltage power supply mode to a low-voltage power supply mode. For example, it can be a signal output by the Vehicle Control Unit (VCU) when certain conditions are met.

[0040] Low-voltage power supply mode refers to the state in which the high-voltage system is in hibernation and the low-voltage system is powered independently.

[0041] Specifically, when the target vehicle enters a static parking state and meets preset conditions (such as no active load demand from the high-voltage system and the low-voltage system being able to meet the current load power consumption), the vehicle controller will generate a low-voltage switching signal. This signal is sent to the execution unit via the control bus, and the execution unit completes the power supply mode switch. After the switch is completed, the high-voltage system and the low-voltage system are physically isolated, and the low-voltage system begins to supply power to the target vehicle independently.

[0042] Optionally, the execution unit can be a relay. The vehicle controller outputs control commands to control the relay to physically switch between high and low voltage power supply paths, thereby switching the power supply mode to a low voltage power supply mode.

[0043] Step S120: Obtain the first state data of the target vehicle.

[0044] The first state data includes low-voltage load power, low-voltage system battery status, and ambient temperature.

[0045] Understandably, the key parameters that determine the sustainable power supply capability of the target vehicle's low-voltage system include: the health status of the low-voltage battery, the capacity of the low-voltage battery, the low-voltage load power (or quiescent current) of the target vehicle, and the ambient temperature.

[0046] Optionally, the low-voltage load power can be the sum of the power consumption of all normally powered devices in the vehicle's static sleep state, such as the standby current of the body controller, anti-theft module, and sensors. After the vehicle enters the low-voltage power supply mode, the total load current is collected in real time by a Hall current sensor deployed on the low-voltage bus, and the low-voltage load power is obtained by combining it with the monitored low-voltage network voltage value.

[0047] In some embodiments, battery status may include the capacity of the low-voltage battery, remaining battery charge, etc. Battery capacity may be at least one of rated capacity, actual usable capacity, and remaining battery charge. Rated capacity can be obtained directly from the battery's factory parameters, while actual usable capacity can be obtained by detecting conductivity. Remaining battery charge can be read from the target vehicle's battery management system or obtained through an ampere-hour integration method combined with open-circuit voltage calibration.

[0048] Alternatively, the ambient temperature can be obtained using a temperature sensor.

[0049] Step S130: Based on the first state data, predict the duration of the low-voltage system.

[0050] The duration is used to represent the theoretical operating time of a low-pressure system under current conditions.

[0051] In some embodiments, the duration of the low-voltage system can be predicted based on the remaining battery power and low-voltage load power in the first state data.

[0052] Since factors such as battery health and ambient temperature can also affect the operating time of low-voltage batteries, these factors can be further taken into account when calculating the operating time.

[0053] In other embodiments, the battery status of the low-voltage system includes the remaining battery charge and battery health.

[0054] For example, the health status of a battery can be calculated from historical cycle data provided by the battery management system, for example, based on a capacity decay model. This disclosure does not specifically limit this, as long as the battery health status can be obtained.

[0055] Correspondingly, based on the first state data, the duration of the low-voltage system is predicted, including: calculating the effective available power of the low-voltage system based on the remaining battery power, battery health, and ambient temperature; and determining the duration of the low-voltage system based on the effective available power and the low-voltage load power.

[0056] Effective available power is used to indicate the actual remaining battery power in a low-voltage system.

[0057] Optionally, predicting the duration of the low-voltage system based on the first state data may include: calculating the actual usable capacity of the low-voltage system based on the battery state and ambient temperature of the low-voltage system in the first state data; obtaining the effective usable charge based on the product of the battery state of charge (SOC) provided by the target vehicle's battery management system and the actual usable capacity; and then obtaining the duration of the low-voltage system based on the effective usable charge and the low-voltage load power. This method can more accurately quantify the actual usable charge of the battery and avoid prediction deviations caused by aging or temperature effects.

[0058] In some embodiments, a calculation model can be established to describe the correspondence between the first state data and the effective available power. Correspondingly, based on the remaining battery power, battery health, and ambient temperature of the low-voltage system, the effective available power of the low-voltage system is calculated, including: inputting the remaining battery power, battery health, and ambient temperature of the low-voltage system into the pre-established calculation model to obtain the effective available power.

[0059] Specifically, a computational model can be established through experimental calibration to quantitatively describe the impact of battery health and ambient temperature on battery capacity degradation. Specifically, for ambient temperature, the relationship between actual discharge capacity and battery capacity is measured at various preset temperatures to establish a mapping relationship between temperature and battery capacity. For battery health, an experimental mapping relationship between battery health and battery capacity degradation is constructed.

[0060] In this embodiment of the disclosure, the influence of battery health and ambient temperature on power decay is quantitatively described by the attenuation coefficient. Correspondingly, based on the remaining battery power, battery health, and ambient temperature of the low-voltage system, the effective available power of the low-voltage system is calculated, including: obtaining the first attenuation coefficient corresponding to the ambient temperature and the second attenuation coefficient corresponding to the battery health, determining the product of the remaining battery power, the first attenuation coefficient, and the second attenuation coefficient of the low-voltage system, and determining the product as the effective available power of the low-voltage system.

[0061] In this embodiment of the disclosure, determining the duration of a low-voltage system based on the effective available power and the low-voltage load power includes: calculating the quotient of the effective available power and the low-voltage load power, and determining it as the duration of the low-voltage system.

[0062] S140 determines the target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage habits.

[0063] The target control scheme is used to control whether the high-voltage system charges the low-voltage system. Its core lies in adjusting the duration of the low-voltage system's charging based on the voltage drop rate of the low-voltage system and user usage habits, making the target control scheme more closely reflect the user's actual vehicle usage patterns and the battery's true state.

[0064] Optionally, the target control scheme may include a charging command and a charging trigger threshold. For example, the target control scheme may include a command to charge immediately or a trigger threshold to charge after a specified number of charging cycles.

[0065] The voltage drop rate is used to represent the change in the low-voltage battery's output voltage per unit time, reflecting the battery's real-time performance. Specifically, when a rapid voltage drop is detected (i.e., a fast voltage drop rate), the target control scheme should be an instruction to charge immediately, so as to promptly control the high-voltage system to charge the low-voltage system and avoid the risk of battery depletion. Conversely, if the voltage drops gradually (i.e., a slow voltage drop rate), no correction is needed.

[0066] User usage habit information reflects the user's usage patterns for the target vehicle. This information can be obtained by acquiring and analyzing the historical usage data of each user for the target vehicle over a period of time.

[0067] Optionally, user usage habit information can be quantitative or patterned information that characterizes user usage patterns, extracted by analyzing historical vehicle usage data (such as parking duration distribution, high-voltage system wake-up intervals, and trip distances). For example, user usage habit information could be long-term parking patterns, high-frequency short-distance patterns, or regular nighttime charging patterns.

[0068] In this embodiment, user usage habit information may include parking duration (e.g., 8 consecutive hours of parking overnight), the ratio of short-distance to long-distance usage (e.g., short-distance usage accounts for 70%), and the temporal pattern of high-voltage system wake-up times. Specifically, for users who frequently use short-distance vehicles, the parking interval is short, and the corrected available duration can be shortened to ensure that the low-voltage battery has sufficient charge when the user uses the vehicle next time, thus improving vehicle reliability. For target vehicles that are parked for a long time, the available duration is increased to maximize the dormancy time of the high-voltage system and reduce static energy consumption.

[0069] Optionally, correction coefficients can be further set, including a first correction coefficient and a second correction coefficient. The target control scheme is comprehensively determined based on the duration, the voltage drop rate of the low-voltage system, user usage information, and the correction coefficients. Specifically, multiple correspondences between voltage drop rates and multiple first correction coefficients, and multiple correspondences between user usage information and multiple second correction coefficients are pre-set; based on the correspondences between multiple voltage drop rates and multiple first correction coefficients, a first correction coefficient corresponding to the current voltage drop rate is determined; and based on the correspondences between multiple user usage information and multiple second correction coefficients, a second correction coefficient corresponding to the current user usage information is determined; the duration is corrected based on the first and second correction coefficients to determine the target control scheme.

[0070] In this embodiment, the correction coefficient may include a positive correction coefficient and a negative correction coefficient. For scenarios where the voltage drop rate of a low-voltage system is slow, a positive correction coefficient can be used to appropriately extend the duration; for scenarios where the voltage drop rate of a low-voltage system is fast, a negative correction coefficient can be used to appropriately shorten the duration. Through this collaborative correction mechanism, simple physical power prediction is transformed into an adaptive management time base that integrates real-time battery characteristics and user behavior patterns, thereby providing accurate input for the subsequent generation of the target control scheme and improving the accuracy of the target control scheme.

[0071] Optionally, a time threshold can be preset to represent the critical time point for charging the high-voltage system. The target control scheme can be determined based on the time threshold. Correspondingly, the target control scheme can be determined based on the duration, the voltage drop rate of the low-voltage system, and user usage information. This includes: correcting the duration based on the voltage drop rate of the low-voltage system and user usage information to obtain a corrected duration; if the corrected duration is less than the time threshold, it indicates that the low-voltage system will be unable to maintain power supply in the short term, and the high-voltage system is controlled to charge the low-voltage system; if the duration is greater than or equal to the time threshold, it indicates that the low-voltage system can still safely supply power in the short term, and it is not necessary to control the high-voltage system to charge the low-voltage system temporarily.

[0072] The technical solution of this embodiment combines the voltage drop rate with user habit information to dynamically decide the charging timing of the high-voltage system, thereby adaptively optimizing the energy management process. It effectively solves the problems of high static energy consumption, poor charging timing (risk of premature wake-up or power depletion) and low overall energy efficiency caused by passive response strategies, significantly reduces unnecessary energy consumption, and ensures continuous and reliable power supply to the low-voltage system.

[0073] Figure 2 The diagram shown is a flowchart illustrating the steps for determining a target control scheme based on duration, voltage drop rate of a low-voltage system, and user usage habits, according to an embodiment of this disclosure. Figure 2 As shown, based on the duration of operation, the voltage drop rate of the low-voltage system, and user usage habits, the target control scheme is determined, which includes the following steps.

[0074] S210 determines the duration of the charging reference cycle based on user usage habit information.

[0075] The charging reference period can be a standardized time unit determined based on user habits. Alternatively, the charging reference period can be determined based on statistical indicators of user habits.

[0076] In some embodiments, the charging reference period can be a period set based on statistical indicators of the user's historical parking time, or a period of time dynamically adjusted according to the frequency of vehicle use. For example, the charging reference period can be a period set based on the median of the user's historical parking time.

[0077] In some embodiments, the charging reference cycle duration can be determined by combining the low-voltage system power capacity, while protecting battery health, in order to predict a charging reference cycle that suits user habits. The specific implementation is described below.

[0078] In this embodiment of the disclosure, determining the duration of the charging reference cycle based on user usage habit information includes: determining the expected parking time or expected usage frequency of the target vehicle based on user usage habit information; and determining the duration of the charging reference cycle based on the expected parking time or expected usage frequency with the goal of maintaining the low-voltage system's power level not lower than a preset health threshold.

[0079] The estimated parking duration or estimated usage frequency reflects the likely duration of the next static phase that the target vehicle is about to enter, or the frequency with which the vehicle will be used in the short term, and is used for short-term predictions of future user behavior.

[0080] The preset health threshold is the lower limit of the low-voltage system's charge level to ensure low-voltage battery life and prevent damage from over-discharge. Specifically, the preset health threshold can be a State of Charge (SOC) percentage; for example, the preset health threshold could be 70%.

[0081] Based on this, with the goal of maintaining the battery level consistently above the preset health threshold, the duration of the charging baseline cycle is calculated based on predicted user behavior. Specifically, within a given predicted time window, the total amount of electricity that the battery can consume to discharge from its current level to the preset health threshold is distributed across several reasonable charge-discharge cycles, thereby determining the maximum duration of each cycle, which is the charging baseline cycle.

[0082] In one specific embodiment, for users who frequently use the vehicle for short distances, the short intervals between vehicle parking allow for a shorter charging baseline cycle, ensuring that the low-voltage battery has sufficient charge when the user uses the vehicle next time, thus improving vehicle reliability. For vehicles intended for long-term parking, the charging baseline cycle can be appropriately increased within the limits of battery health to maximize the dormancy time of the high-voltage system and reduce static energy consumption.

[0083] For example, based on user usage habit information, it is determined that the user typically parks the vehicle during a first preset time period (e.g., 10 PM to 8 AM), and the expected parking duration is the duration corresponding to the first preset time period (e.g., 10 hours). Alternatively, based on user usage habit information, it is determined how many times the user typically uses the vehicle every second preset time period (e.g., 2-3 hours). If this number is higher than the preset number of uses (e.g., 2 times), the user's expected usage frequency is determined to be high. Furthermore, while ensuring that the battery charge never falls below a preset health threshold, the longest allowable discharge time period is determined based on the user's expected parking duration or expected usage frequency, and the duration of the charging reference cycle is determined based on this longest allowable discharge time period.

[0084] Optionally, machine learning can be used to analyze users' historical usage data (such as vehicle parking duration distribution and high voltage wake-up frequency) to identify user patterns (such as frequent short-distance mode or long-term parking mode). With the goal of maintaining the low voltage power level above the health threshold (such as 70%), if it is a long-term parking mode, for example, if the expected parking time is 10 hours, a longer charging baseline cycle can be set, such as 5 hours. If it is a short-distance frequent use mode, a shorter charging baseline cycle can be set, such as 2 hours.

[0085] The technical solution of this disclosure embodiment, based on preset health thresholds and user usage habit information, determines a charging reference cycle, which not only achieves energy saving for the whole vehicle, but also maximizes the protection of the battery, achieving the dual goals of immediate energy efficiency optimization and long-term battery life protection, taking into account both immediate efficiency and long-term sustainability.

[0086] S220 quantifies the available duration into the equivalent number of remaining energy cycles in units of the charging reference cycle, based on the duration of the charging reference cycle.

[0087] Equivalent remaining energy cycles can be a quantitative indicator that converts the available duration into standardized cycles, reflecting the number of times the low-voltage battery's energy can support a user in completing their usual scenarios. For example, the battery capacity is expected to support the user in completing approximately 3.5 of their usual parking cycles.

[0088] Alternatively, the equivalent remaining energy cycle number can be expressed as the duration of the charge reference cycle divided by the duration of the charge reference cycle.

[0089] S230 generates a target control scheme based on the equivalent remaining energy cycle number, user usage habits, and the voltage drop rate of the low-voltage system.

[0090] In some embodiments, the high-voltage system is controlled to charge the low-voltage system if any of the following conditions are met: the equivalent remaining energy cycle count is less than a preset threshold, or the voltage of the low-voltage system drops rapidly. Specifically, if the equivalent remaining energy cycle count is less than the preset threshold, it indicates that the low-voltage battery is about to run out of power, and the high-voltage system needs to be controlled to charge the low-voltage system; if the voltage drops rapidly, it may mean that the battery is aging or there is an unexpected load, and the high-voltage system also needs to be controlled to charge the low-voltage system.

[0091] If the user's usage habits indicate a frequent short-distance driving pattern, a target control scheme with a higher charging frequency can be selected. Conversely, if the user's usage habits suggest the vehicle is about to enter a long-term parking phase, a target control scheme with a lower charging frequency can be selected.

[0092] Optionally, multiple equivalent remaining energy cycles, multiple user usage habit information, multiple low-voltage system voltage drop rates, and multiple preset control schemes can be set to generate corresponding target control schemes based on the preset correspondence, equivalent remaining energy cycles, user usage habit information, and low-voltage system voltage drop rates.

[0093] The technical solution of this embodiment determines a personalized baseline cycle duration based on user habits, then converts the predicted available duration into an equivalent number of remaining energy cycles, and finally combines the equivalent number of remaining energy cycles, user habits, and voltage trends to generate a control scheme. This provides a calculation of the number of remaining available scenarios based on typical user usage scenarios, which significantly improves the personalization and scenario fit of charging timing decisions, effectively solves the problem that fixed strategies cannot adapt to diverse user habits, and further optimizes vehicle energy management.

[0094] In this embodiment of the disclosure, a target control scheme is generated based on the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system. This includes generating the target control scheme based on at least one preset rule from a preset rule set, using the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system as conditions.

[0095] The preset rule set may include multiple equivalent remaining energy cycle numbers, multiple user usage habit information, multiple low-voltage system voltage drop rates, and preset correspondences between multiple preset control schemes.

[0096] Optionally, the preset rule set is a collection of predefined logical judgment statements, which may include multiple conditions to be met and actions corresponding to each condition. For example, it may include specific combinations of conditions consisting of the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system, as well as target control schemes corresponding to each combination of conditions.

[0097] Optionally, the specific form of the preset rule set can be a simple decision tree or a complex expert system, and this disclosure does not specifically limit it.

[0098] Specifically, the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate of the low-voltage system are used as conditional input values ​​and compared with the condition part of each rule in the preset rule set. If a specific rule in the preset rule set is satisfied, the rule is triggered, and the target control scheme corresponding to the rule is generated.

[0099] The technical solution of this embodiment generates a target control scheme by using a preset rule set, with the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate as judgment conditions. This transforms the multivariate and nonlinear prediction problem into a structured logical judgment process, achieving systematization and high reliability in the generation of control schemes, and giving the target control scheme good interpretability and scalability.

[0100] In some embodiments, the preset rule set includes at least one of the following preset rules: if the equivalent remaining energy cycle number is less than a first threshold and the voltage drop rate is greater than a second threshold, a target instruction indicating immediate charging is generated; if the user uses habit information to indicate that the target vehicle is about to enter a long-term parking mode and the equivalent remaining energy cycle number is greater than a third threshold, a target trigger threshold indicating a first charging cycle is generated; if the voltage drop rate is less than a fourth threshold, a target trigger threshold indicating a second charging cycle is generated, wherein the duration of the first charging cycle is greater than the duration of the second charging cycle.

[0101] The first, second, third, and fourth thresholds can be pre-defined numerical critical points used to distinguish different states. Specifically, the first threshold can be a critical value used to distinguish whether the equivalent remaining energy is sufficient, for example, it can be 1, 2, or 3. The second threshold can be a critical value used to distinguish between fast and slow voltage change rates, for example, it can be 0.04V / h, 0.03V / h, or 0.05V / h.

[0102] The third threshold can be a critical value used to determine whether the battery power is sufficient to support the static load of the target vehicle under long-term parking mode; for example, it could be 4, 5, or 6. The fourth threshold can be a critical value used to distinguish between slow and not slow voltage drop rates; for example, it could be 0.01V / h, 0.02V / h, or 0.025V / h.

[0103] The target instruction can be a command sent directly to the actuator, requiring the high-voltage system to be woken up immediately and controlled to charge the low-voltage system.

[0104] Specifically, if the equivalent remaining energy cycle count is less than the first threshold and the voltage drop rate is greater than the second threshold, it indicates that the low-voltage system has low remaining battery power and the battery voltage is still dropping rapidly. The battery is about to run out of power and is in poor condition, requiring immediate intervention, and a target instruction to charge immediately is generated. If user usage information indicates that the target vehicle is about to enter a long-term parking mode and the equivalent remaining energy cycle count is greater than the third threshold, it indicates that the user will not use the vehicle for a long time and the current battery power is very sufficient. In this case, a relatively long trigger threshold (i.e., the first charging cycle) can be set to allow the high-voltage system to enter a long-term sleep mode, maximizing the saving of static energy consumption. If the voltage drop rate is less than the fourth threshold, a target trigger threshold indicating the second charging cycle is generated. A voltage drop rate less than the fourth threshold indicates that the current voltage drop is relatively slow, indicating that the battery is in good condition, the load is stable, and the environment is mild. In this case, a relatively short trigger threshold (i.e., the second charging cycle) can be used to achieve a good balance between energy saving and responsiveness.

[0105] The technical solution of this embodiment converts the equivalent remaining energy cycle number, voltage drop rate and user usage habit information into discrete numerical information by setting different thresholds. Each rule is for a typical scenario and outputs a control strategy, which simultaneously realizes the safety net to prevent battery depletion, maximizes the reduction of static energy consumption and optimizes system operating efficiency.

[0106] In some embodiments, the preset rule set includes a fuzzy rule base. Based on at least one preset rule in the preset rule set, and using the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate of the low-voltage system as conditions, a target control scheme is generated. This includes: mapping the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate to corresponding fuzzy semantic levels; and inputting the fuzzy semantic levels corresponding to the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate into the fuzzy rule base for inference to obtain the target control scheme.

[0107] A fuzzy rule base can be a set of decision rules that use fuzzy logic to process uncertain inputs, and is used to map continuous variables to semantic control strategies.

[0108] Fuzzy semantic levels are used to transform continuous, precise numerical values ​​into more flexible conceptual descriptions. They can use qualitative terms from natural language to describe the degree or range to which a precise numerical value belongs. For example, large, medium, small; frequent, average, few; fast, flat, slow, etc.

[0109] In this embodiment of the disclosure, based on the numerical range corresponding to the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate, the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate are respectively mapped to corresponding fuzzy semantic levels. Specifically, based on the numerical range corresponding to the equivalent remaining energy cycle number, the equivalent remaining energy cycle number is mapped to large, medium, and small; based on the numerical range corresponding to the voltage change per unit time, the voltage drop rate is mapped to fast, flat, and slow; and based on the numerical range corresponding to user usage habit information (e.g., parking duration), the user usage habit information is mapped to long-term, medium-term, and short-term.

[0110] Furthermore, based on the equivalent remaining energy cycle number, user usage habit information, and the fuzzy semantic level corresponding to the voltage drop rate, it is determined whether the conditions of each rule in the fuzzy rule base are met, and all the satisfied rules are obtained as target rules; a target control scheme is generated based on the control schemes corresponding to all target rules.

[0111] Specifically, the fuzzy semantic levels corresponding to the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate are input into a fuzzy rule base for inference to obtain the target control scheme. This includes: if the fuzzy semantic level corresponding to the equivalent remaining energy cycle number is small and the fuzzy semantic level corresponding to the voltage drop rate is fast, then the target control scheme is to control the high-voltage system to charge the low-voltage system. If the fuzzy semantic level corresponding to the user usage habit information is long-term and the fuzzy semantic level corresponding to the equivalent remaining energy cycle number is medium, then the target control scheme is to control the high-voltage system to temporarily not charge the low-voltage system. If the fuzzy semantic level corresponding to the voltage drop rate is slow, then the target control scheme is to control the high-voltage system to temporarily not charge the low-voltage system.

[0112] Optionally, the control scheme corresponding to all target rules is used to control the high-voltage system to charge the low-voltage system, including: determining the number of each control scheme based on the control scheme corresponding to each target rule, so as to obtain a large number of control schemes, and generating a target control scheme.

[0113] Optionally, the control scheme corresponding to all target rules is to control the high-voltage system to charge the low-voltage system, including: if there is a control scheme corresponding to any target rule that controls the high-voltage system to charge the low-voltage system, then the target control scheme is determined to be to control the high-voltage system to charge the low-voltage system.

[0114] The technical solution of this embodiment maps the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate into fuzzy semantic levels; and performs fuzzy reasoning based on these fuzzy semantics to finally obtain an optimized target control scheme. This reduces the decision jumps or oscillations that may occur based on the rule set of precise thresholds, and improves the adaptability, decision smoothness, and robustness of the vehicle energy management strategy in complex real-world scenarios.

[0115] Figure 3 The diagram shown is a flowchart illustrating a vehicle energy management method according to another embodiment of this disclosure. Figure 3 As shown, the vehicle energy management method specifically includes the following steps.

[0116] S310, in response to a low-voltage switching signal, switches the target vehicle to low-voltage power supply mode.

[0117] S320, acquire the first state data of the target vehicle.

[0118] The first state data includes low-voltage load power, low-voltage system battery status, and ambient temperature.

[0119] S330, based on first-state data, predicts the duration of the low-voltage system.

[0120] S340 determines the target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage habits.

[0121] The S350, based on a target control scheme, controls the high-voltage system to charge the low-voltage system.

[0122] Optionally, the target control scheme may include a charging command, which may include the time for the high-voltage system to charge the low-voltage system. Correspondingly, based on the target control scheme, controlling the high-voltage system to charge the low-voltage system includes: when the charging time corresponding to the charging command is reached, controlling the high-voltage system to charge the low-voltage system.

[0123] Understandably, the duration is a theoretical value derived from predictions and may not cover unforeseen circumstances (such as abnormal power consumption by unknown loads, sudden degradation of battery performance, or exposure to extreme environments). Therefore, parallel charging conditions can be set. When any charging condition is met, the high-voltage system is controlled to charge the low-voltage system to ensure the reliability and safety of the control scheme.

[0124] In this embodiment of the disclosure, based on the target control scheme, controlling the high-voltage system to charge the low-voltage system includes: counting the cumulative number of cycles experienced by the low-voltage system since the last charging using a counter; controlling the high-voltage system to charge the low-voltage system when the cumulative number of cycles is greater than or equal to the charging trigger threshold; and controlling the high-voltage system to charge the low-voltage system when the voltage of the low-voltage system is less than the voltage threshold.

[0125] The target control scheme may include a charging trigger threshold. This charging trigger threshold represents the theoretical charging timing calculated based on the current state and user usage habits; for example, it may be the number of charging reference cycles.

[0126] Specifically, during execution, a counter continuously accumulates the number of complete charging reference cycles experienced by the low-voltage system since the last charging completion, obtaining the cumulative cycle count. When the cumulative cycle count is greater than or equal to the charging trigger threshold, it is determined that the planned charging time has been reached, and the high-voltage system is then triggered to start the charging process. This path achieves precise execution of the intelligent decision-making scheme.

[0127] In this embodiment of the disclosure, a voltage threshold is set to prevent over-discharge damage to the battery, and a parallel charging condition is established based on the voltage threshold. Specifically, during execution, the real-time voltage of the low-voltage system is continuously monitored and compared with the voltage threshold. Once the low-voltage system voltage is detected to be lower than the voltage threshold, regardless of the current cumulative cycle count or whether the predicted charging trigger threshold has been reached, the high-voltage system will be immediately and unconditionally triggered to start charging.

[0128] In this embodiment of the present disclosure, the counter is reset to zero after each charging operation is completed in preparation for the next round of management cycle counting.

[0129] The technical solution of this embodiment, by setting a trigger path for cycle counting based on intelligent decision-making and a trigger path for voltage protection guaranteed by direct physical monitoring, avoids the failure of the target control scheme with predictable duration, uses the voltage threshold as an emergency backup, ensures the reliability and safety of vehicle energy management, and prevents the risk of missed triggers.

[0130] In this embodiment of the disclosure, the vehicle energy management method further includes: switching the target vehicle to a high-voltage power supply mode in response to a high-voltage switching signal; acquiring second state data of the target vehicle, the second state data including the remaining battery power of the high-voltage system; and dynamically adjusting the power output weight of the high-voltage system between the drive system and the body accessory system of the target vehicle based on the remaining battery power of the high-voltage system.

[0131] Understandably, the high-voltage system is activated to supply power during the vehicle's operation. Different control objectives need to be achieved in different scenarios (e.g., power performance, comfort, and range). To optimize power resource utilization, the internal energy distribution under high-voltage power supply mode can be adjusted based on the real-time energy state of the high-voltage battery to resolve energy distribution conflicts between different control objectives and achieve optimized energy management under high-voltage power supply mode.

[0132] The second state data describes a set of parameters representing the current energy state and capability of the high-voltage system under high-voltage power supply mode. In this embodiment, the second state data includes the remaining battery capacity of the high-voltage system. Correspondingly, obtaining the second state data of the target vehicle includes: obtaining the state of charge (SOC) of the high-voltage system battery through the battery management system. Further, the actual remaining battery capacity of the high-voltage system is obtained based on the product of the battery SOC and the actual usable capacity of the high-voltage system battery.

[0133] The drive system is primarily responsible for power output, converting electrical energy into mechanical energy to propel the vehicle. A drive system typically includes a drive motor, motor controller (inverter), reducer, and related sensors and control software. Its power requirements are directly related to driver pedal commands, vehicle speed, and gradient.

[0134] Body accessory systems refer to loads other than the drive system that are directly or indirectly powered by a high-voltage system. Body accessory systems typically include thermal management systems and entertainment assistance systems, such as electric air conditioning compressors (cooling), heaters (heating), and audio / video players.

[0135] Power output weight represents the total available power or total output power ratio of the high-voltage system. In this disclosure, power output weight represents the distribution ratio or priority relationship of the total output power between the two types of loads: the drive system and the body accessory system.

[0136] Optionally, a mapping relationship between the remaining battery capacity and the allocation weight is pre-established so as to dynamically adjust the power output weight of the high-voltage system between the drive system and the body accessory system of the target vehicle based on the remaining battery capacity of the high-voltage system and the mapping relationship.

[0137] In this embodiment, the power output weight of the high-voltage system between the drive system and the vehicle's accessory systems is dynamically adjusted based on the different ranges of the remaining battery charge in the high-voltage system. Specifically, for high-charge scenarios (e.g., SOC greater than 80%), the power output weight can balance power and comfort, allowing accessory systems (such as air conditioning and seat heating) to operate at higher power, and the driving mode can remain in standard or sport mode to provide ample power. For medium-charge scenarios (e.g., 30% greater than SOC and less than or equal to 80%), the power output weight can favor comfort, switching the driving mode to standard mode. For low-charge scenarios (e.g., SOC less than or equal to 30%), the power output weight needs to favor range, and unnecessary comfort-oriented high-voltage accessories (such as air conditioning cooling / heating functions) can be turned off or significantly limited, and the drive system enters energy-saving or power-limiting mode to ensure that the vehicle can maintain operation with minimal energy consumption.

[0138] Optionally, weight adjustment can be achieved through a controller using lookup tables, linear interpolation, or optimization algorithms based on fuzzy logic. The output includes the power ratios of the drive system and the body accessory system.

[0139] In some scenarios, such as low-battery scenarios, to balance energy efficiency and driving experience, a gradual power limitation can be adopted. The system does not directly switch between standard mode (power performance) and economy mode (range), but rather smoothly switches between high power and low energy consumption. Therefore, in this embodiment of the disclosure, based on the remaining battery charge of the high-voltage system, a transition curve is generated by linear interpolation between the standard (power performance) power curve and the economy (low energy consumption) power curve. Based on this transition curve, the power output weight of the high-voltage system between the target vehicle's drive system and body accessory systems is dynamically adjusted.

[0140] For example, a standard power curve represents the performance setting of a target vehicle in standard or power mode. The horizontal axis is typically the accelerator pedal opening (representing the driver's power request), and the vertical axis is typically the electric motor output torque (representing the vehicle's actual response). This curve is relatively steep, indicating a strong power response even with light throttle input, aiming for driving pleasure.

[0141] The economic power curve represents the performance setting of the target vehicle in economy or energy-saving mode. This curve is relatively flat; at the same accelerator pedal opening, it outputs less torque than the standard power curve, in order to complete the acceleration process with the least amount of energy, pursuing energy efficiency.

[0142] Linear interpolation, on the other hand, uses linear calculations to find the midpoint between the standard dynamic curve and the economic dynamic curve between these two known curves. These midpoints form multiple transition curves between the standard dynamic curve and the economic dynamic curve.

[0143] Specifically, based on the remaining battery charge of the high-voltage system (or other parameters such as driving style and navigation conditions), the higher the remaining battery charge, the closer the transition curve is to the standard power curve; the lower the remaining battery charge, the closer the transition curve is to the economic power curve. Furthermore, the VCU will use this transition curve as a new torque mapping table. When the driver depresses the accelerator pedal, it will determine how much torque to output to the drive system based on the pedal opening and this transition curve, in order to smoothly limit torque.

[0144] Optionally, multiple loads in the vehicle body accessory system can be prioritized according to their individual functions. The power of each load can be adjusted based on this priority, reducing the power supply to non-critical high-voltage loads to ensure the power requirements of the drive system and the stability of the high-voltage bus voltage. Specifically, the high-voltage bus voltage is monitored in real time; when a voltage drop exceeding a preset threshold is detected within a short period, a request to reduce power or suspend operation is sent to the controllers of lower-priority accessories and then to the controller of the vehicle body accessory system, according to the preset accessory priorities. This request is released once the voltage recovers.

[0145] Optionally, the priority settings can be as follows: The entertainment system screen and ambient lighting are set as the first priority (lowest priority), and their power is reduced first. Seat heating / ventilation and steering wheel heating are set as the second priority; the air conditioning compressor as the third priority; and electric power steering and brake assist as the fourth priority (highest priority), ensuring output power as much as possible. For example, if a driver's rapid acceleration request causes a sudden drop in high-voltage bus voltage exceeding 5%, a request to reduce power or suspend operation is sent to the controller of the vehicle accessory systems according to a preset priority (e.g., seat heating > air conditioning compressor > entertainment system). After acceleration ends and the high-voltage bus voltage stabilizes, the power of the reduced accessories is gradually and orderly restored.

[0146] The technical solution of this embodiment, when the vehicle switches to high-voltage power supply mode, establishes a dynamic mapping relationship between power and power distribution weights. This allows for priority protection of performance and comfort in the high power range, while automatically tilting towards the drive system in the low power range to prioritize range protection. This effectively solves the energy distribution contradiction between power, comfort and range during high-voltage power supply, optimizes the overall energy efficiency of the vehicle during driving, and achieves refined and adaptive energy management in high-voltage mode.

[0147] The above embodiments illustrate the vehicle energy management method in detail. The following will combine... Figure 4 This section details the specific process of vehicle energy management based on the aforementioned vehicle energy management principles.

[0148] Figure 4 The diagram shown is a schematic flowchart of a vehicle energy management method provided in another embodiment of this disclosure. Figure 4As shown, the vehicle energy management method of this disclosure includes the following steps.

[0149] S410, the target vehicle has been detected to have entered static parking mode.

[0150] S420 determines whether the low-voltage switching signal is satisfied.

[0151] If the low-voltage switching signal is satisfied, then execute S430; if the low-voltage switching signal is not satisfied, then execute S440.

[0152] S430 switches the target vehicle to low-voltage power supply mode.

[0153] In this embodiment, a high-voltage and low-voltage power supply path switching is achieved through an energy routing controller. Specifically, the energy routing controller includes a relay group, a current sensor, and a microprocessor, and communicates with the vehicle controller via a CAN bus.

[0154] Specifically, when a low-voltage switching signal is generated, the control relay group disconnects the high-voltage power supply circuit and closes the low-voltage independent power supply circuit, so that the target vehicle enters a low-voltage power supply mode in which the low-voltage battery powers the regular parking load.

[0155] S440 controls the target vehicle to remain in a static parking mode. At this time, the high-voltage system continuously supplies power to the target vehicle.

[0156] S450, acquire the first state data of the target vehicle.

[0157] The first state data includes low-voltage load power, low-voltage system battery status, and ambient temperature.

[0158] Specifically, the load current of the low-voltage system is collected in real time by a current sensor, and the low-voltage load power (P_load) is calculated by combining it with the low-voltage bus voltage. The battery status of the low-voltage system is obtained through the battery management system, which includes at least the remaining battery capacity (Q_batt) and battery health (SOH). The ambient temperature (T) is obtained through an on-board temperature sensor. The low-voltage load power, the battery status of the low-voltage system, and the ambient temperature are used as the first state data, and the first state data is transmitted to the microprocessor of the energy routing controller via the CAN bus.

[0159] S460, based on the first state data, predicts the duration of the low-voltage system and based on the duration.

[0160] First, based on the remaining battery capacity, battery health, and ambient temperature of the low-voltage system, the effective available capacity of the low-voltage system is calculated. Specifically, the temperature influence coefficient (η(T)) and the battery health decay coefficient (k(SOH)) are obtained; the product of the remaining battery capacity (Q_batt), the temperature influence coefficient (η(T)), and the battery health decay coefficient (k(SOH)) is determined as the effective available capacity (Q_available) of the low-voltage system.

[0161] Then, based on the available power and low-voltage load power, the duration of the low-voltage system is determined. Specifically, the available power (Q_available) and low-voltage load power (P_load) are determined as the duration (T_available) of the low-voltage system.

[0162] S470 generates a target control scheme based on a fuzzy rule base, using the duration, user habits, and voltage drop rate of the low-voltage system as conditions.

[0163] First, historical vehicle usage data is analyzed through machine learning to generate user usage habit information, which may include vehicle parking time distribution patterns and the ratio of short-distance to long-distance usage frequency.

[0164] Secondly, the duration of the charging baseline cycle is determined based on user usage habits. For example, for users who park their vehicles for extended periods overnight, T_base can be set to 5 hours; for users who frequently use their vehicles for short trips, the charging baseline cycle (T_base) can be set to 2 hours.

[0165] Then, the quotient of the available duration (T_available) and the duration of the charging base cycle (T_base) is determined as the equivalent remaining energy cycle number (N_equiv). Finally, the low-voltage battery voltage value is continuously monitored for multiple monitoring cycles, and the voltage change rate (ΔV / Δt) per unit time is calculated. Based on the comparison between (ΔV / Δt) and a preset threshold, the voltage drop rate is classified into three levels: fast, medium, and slow. The equivalent remaining energy cycle number (N_equiv), user usage information, and voltage drop rate are mapped to corresponding fuzzy semantic levels. The fuzzy semantic levels corresponding to the equivalent remaining energy cycle number, user usage information, and voltage drop rate are input into the fuzzy rule base for inference to obtain the target control scheme.

[0166] The target control scheme includes two forms: one is an immediate charging instruction; the other is a specific charging trigger threshold (N_opt).

[0167] S480: When the cumulative number of cycles is greater than or equal to the charging trigger threshold, or when the voltage of the low-voltage system is less than the voltage threshold, the high-voltage system is controlled to charge the low-voltage system.

[0168] Specifically, the cumulative number of cycles is obtained by counting with a counter. When the cumulative number of cycles is greater than or equal to the charging trigger threshold, or when the voltage of the low-voltage system is less than the voltage threshold, the high-voltage system is controlled to charge the low-voltage system.

[0169] In this embodiment, if the target control scheme is an immediate charging command, the high-voltage system is directly woken up for charging. If the target control scheme is a charging trigger threshold (N_opt), the following dual-condition triggering logic is executed: a counter is used to count the cumulative number of cycles experienced by the low-voltage system since the last charging, and the cumulative number of cycles is continuously compared with the charging trigger threshold (N_opt). If the cumulative number of cycles is detected to be greater than or equal to (N_opt), it is determined that the predicted charging timing has been reached, and the high-voltage system is controlled to wake up and charge the low-voltage system.

[0170] Simultaneously, the voltage of the low-voltage system is monitored in real time and compared with a preset voltage safety lower limit threshold (V_th). When the voltage of the low-voltage system is less than V_th, the high-voltage system is immediately triggered to charge, regardless of the cumulative cycle number.

[0171] After each high-voltage system completes charging of the low-voltage system, the counter is reset to zero, the high-voltage system goes into sleep mode again according to the strategy, the vehicle returns to low-voltage power supply mode, and waits for the next cycle.

[0172] The above text combined Figures 1 to 4 The present disclosure describes in detail the method embodiments, which are then combined with the following. Figure 5 The present disclosure provides a detailed description of the apparatus embodiments. Furthermore, it should be understood that the descriptions of the method embodiments correspond to the descriptions of the apparatus embodiments; therefore, any parts not described in detail can be found in the foregoing method embodiments.

[0173] Figure 5 The diagram shown is a structural schematic of a vehicle energy management device according to an embodiment of this disclosure. Figure 5 As shown, the vehicle energy management device provided in this embodiment includes: a switching module 501, an acquisition module 502, a prediction module 503, and a control module 504.

[0174] The switching module 501 is configured to switch the target vehicle to a low-voltage power supply mode in response to a low-voltage switching signal.

[0175] The acquisition module 502 is configured to acquire first state data of the target vehicle, including low-voltage load power, low-voltage system battery status, and ambient temperature.

[0176] The prediction module 503 is configured to predict the duration of the low-voltage system based on the first state data.

[0177] The control module 504 is configured to determine a target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage information. The target control scheme is used to control whether the high-voltage system charges the low-voltage system.

[0178] In some embodiments, the control module 504 is configured to: determine the duration of a charging reference cycle based on user usage habit information; quantify the available duration into the equivalent remaining energy cycle number in units of the charging reference cycle based on the duration of the charging reference cycle; and generate a target control scheme based on the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system.

[0179] In some embodiments, the control module 504 is further configured to generate a target control scheme based on at least one preset rule in a preset rule set, using the equivalent remaining energy cycle number, user usage habit information, and the voltage drop rate of the low-voltage system as conditions.

[0180] In some embodiments, the control module 504 is further configured to map the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate to corresponding fuzzy semantic levels; input the fuzzy semantic levels corresponding to the equivalent remaining energy cycle number, user usage habit information, and voltage drop rate to a fuzzy rule base for inference to obtain the target control scheme.

[0181] In some embodiments, the preset rule set includes at least one of the following preset rules: if the equivalent remaining energy cycle number is less than a first threshold and the voltage drop rate is greater than a second threshold, a target instruction indicating immediate charging is generated; if the user uses habit information to indicate that the target vehicle is about to enter a long-term parking mode and the equivalent remaining energy cycle number is greater than a third threshold, a target trigger threshold indicating a first charging cycle is generated; if the voltage drop rate is less than a fourth threshold, a target trigger threshold indicating a second charging cycle is generated, wherein the duration of the first charging cycle is greater than the duration of the second charging cycle.

[0182] In some embodiments, the control module 504 is further configured to determine the expected parking duration or expected usage frequency of the target vehicle based on user usage habit information; and to determine the duration of the charging reference cycle based on the expected parking duration or expected usage frequency with the goal of maintaining the low-voltage system's charge level above a preset health threshold.

[0183] In some embodiments, the control module 504 is further configured to control the high-voltage system to charge the low-voltage system based on a target control scheme; wherein, controlling the high-voltage system to charge the low-voltage system based on the target control scheme includes: counting the cumulative number of cycles experienced by the low-voltage system since the last charging using a counter; controlling the high-voltage system to charge the low-voltage system when the cumulative number of cycles is greater than or equal to a charging trigger threshold; and controlling the high-voltage system to charge the low-voltage system when the voltage of the low-voltage system is less than a voltage threshold.

[0184] In some embodiments, the prediction module 503 is further configured to calculate the effective available power of the low-voltage system based on the remaining battery power, battery health, and ambient temperature of the low-voltage system; and to determine the duration of the low-voltage system based on the effective available power and the low-voltage load power.

[0185] In some embodiments, the control module 504 is further configured to, in response to a high-voltage switching signal, switch the target vehicle to a high-voltage power supply mode; acquire second state data of the target vehicle, the second state data including the remaining battery power of the high-voltage system; and, based on the remaining battery power of the high-voltage system, dynamically adjust the power output weight of the high-voltage system between the drive system and the body accessory system of the target vehicle.

[0186] Below, for reference Figure 6 This describes a vehicle energy management system according to embodiments of the present disclosure. Figure 6 The diagram shown is a structural schematic of a vehicle energy management system provided in an exemplary embodiment of this disclosure.

[0187] like Figure 6 As shown, the vehicle energy management system 60 includes a relay 601 for switching between low-voltage power supply mode and high-voltage power supply mode; a current sensor 602 for collecting the current of the high-voltage system and the low-voltage system; and a processor 603 for implementing the vehicle energy management method of the above embodiment.

[0188] Alternatively, relay 601 may be a group of relays.

[0189] The current sensor 602 can be a high-precision current sensor.

[0190] The processor 603 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the vehicle energy management system 60 to perform desired functions.

[0191] Optionally, the vehicle energy management system may further include a memory 604. This memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 603 may execute these instructions to implement the vehicle energy management methods of the various embodiments of this disclosure described above, and / or other desired functions.

[0192] Of course, for the sake of simplicity, Figure 6 Only some of the components of the vehicle energy management system 60 relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the vehicle energy management system 60 may include any other suitable components depending on the specific application.

[0193] In addition to the methods and apparatus described above, embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the vehicle energy management methods according to various embodiments of this disclosure as described above.

[0194] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0195] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the vehicle energy management methods according to various embodiments of this disclosure described above.

[0196] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0197] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the specific details described above.

[0198] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0199] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions to this disclosure.

[0200] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0201] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A vehicle energy management method, characterized in that, Applied to a target vehicle, the target vehicle including a high-voltage system and a low-voltage system, the method includes: In response to a low-voltage switching signal, the target vehicle is switched to a low-voltage power supply mode; Acquire first state data of the target vehicle, the first state data including low-voltage load power, battery status of the low-voltage system, and ambient temperature; Based on the first state data, the duration of the low-pressure system is predicted; Based on the duration, the voltage drop rate of the low-voltage system, and user usage information, a target control scheme is determined. The target control scheme is used to control whether the high-voltage system charges the low-voltage system.

2. The method according to claim 1, characterized in that, The determination of the target control scheme based on the duration, the voltage drop rate of the low-voltage system, and user usage habits includes: Based on the user usage habit information, the duration of the charging reference cycle is determined; Based on the duration of the charging reference cycle, the available duration is quantified as the equivalent number of remaining energy cycles in units of the charging reference cycle. The target control scheme is generated based on the equivalent remaining energy cycle number, the user usage habit information, and the voltage drop rate of the low-voltage system.

3. The method according to claim 2, characterized in that, The step of generating the target control scheme based on the equivalent remaining energy cycle number, the user usage habit information, and the voltage drop rate of the low-voltage system includes: The target control scheme is generated based on at least one preset rule from the preset rule set, using the equivalent remaining energy cycle number, the user usage habit information, and the voltage drop rate of the low-voltage system as conditions.

4. The method according to claim 3, characterized in that, The preset rule set includes a fuzzy rule base. The step of generating the target control scheme based on at least one preset rule from a preset rule set, using the equivalent remaining energy cycle number, the user usage habit information, and the voltage drop rate of the low-voltage system as conditions, includes: The equivalent remaining energy cycle number, the user usage habit information, and the voltage drop rate are respectively mapped to corresponding fuzzy semantic levels; The equivalent remaining energy cycle number, the user usage habit information, and the fuzzy semantic level corresponding to the voltage drop rate are input into the fuzzy rule base for reasoning to obtain the target control scheme.

5. The method according to claim 3, characterized in that, The preset rule set includes at least one of the following preset rules: If the equivalent remaining energy cycle number is less than the first threshold and the voltage drop rate is greater than the second threshold, then a target command indicating immediate charging is generated. If the user usage habit information indicates that the target vehicle is about to enter a long-term parking mode and the equivalent remaining energy cycle number is greater than the third threshold, then a target trigger threshold indicating the first charging cycle is generated. If the voltage drop rate is less than a fourth threshold, a target trigger threshold indicating a second charging cycle is generated, wherein the duration of the first charging cycle is greater than the duration of the second charging cycle.

6. The method according to claim 2, characterized in that, Determining the duration of the charging baseline cycle based on the user usage habit information includes: Based on the user's usage habit information, determine the expected parking duration or expected usage frequency of the target vehicle; With the goal of maintaining the power of the low-voltage system at or above a preset health threshold, the duration of the charging reference cycle is determined based on the expected parking time or the expected usage frequency.

7. The method according to claim 1, characterized in that, Also includes: Based on the target control scheme, the high-voltage system is controlled to charge the low-voltage system; The step of controlling the high-voltage system to charge the low-voltage system based on the target control scheme includes: The low-voltage system is counted cumulatively since its last charge using a counter. When the cumulative number of cycles is greater than or equal to the charging trigger threshold, the high-voltage system is controlled to charge the low-voltage system. When the voltage of the low-voltage system is less than the voltage threshold, the high-voltage system is controlled to charge the low-voltage system.

8. The method according to claim 1, characterized in that, The battery status of the low-voltage system includes the remaining battery power and battery health. The step of predicting the duration of the low-voltage system based on the first state data includes: Based on the remaining battery power of the low-voltage system, the battery health status, and the ambient temperature, calculate the effective available power of the low-voltage system. The duration of the low-voltage system is determined based on the available power and the low-voltage load power.

9. The method according to claim 1, characterized in that, Also includes: In response to the high-voltage switching signal, the target vehicle is switched to high-voltage power supply mode; Acquire second state data of the target vehicle, the second state data including the remaining battery power of the high-voltage system; Based on the remaining battery power of the high-voltage system, the power output weight of the high-voltage system between the drive system and the body accessory system of the target vehicle is dynamically adjusted.

10. A vehicle energy management system, characterized in that, include: Relays are used to switch between low-voltage and high-voltage power supply modes. Current sensors are used to collect current in high-voltage and low-voltage systems; A processor for implementing the method as described in any one of claims 1 to 9.

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