A multi-role battery management method and service platform based on a service platform

Abstract

The application discloses a kind of battery management methods and service platform based on multi-role service platform, it is related to battery management technical field, and its technical solution key points include the following steps: according to the vehicle actual endurance mileage of target new energy vehicle, the battery energy deployment system corresponding to target new energy vehicle is obtained;The battery energy deployment system includes deployment factor area, abnormal deployment area and deployment result area;Wherein, the deployment factor area includes battery standard deployment factor and deployment weight;The abnormal deployment area includes abnormal deployment characteristic factor and abnormal deployment diagnostic factor;The battery energy data of target new energy vehicle, battery energy deployment system, battery standard deployment factor, deployment weight and vehicle actual endurance mileage are handled and analyzed to obtain the vehicle evaluation endurance mileage of target new energy vehicle;Effect is to make vehicle owner whole process master new energy battery replacement service dynamic.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and more specifically, to a multi-role battery management method and service platform based on a service platform. Background Technology

[0002] As a core component of new energy vehicles, the demand for maintenance and replacement services for vehicle batteries is increasing daily. When new energy vehicles experience issues such as insufficient battery range or performance degradation, customers need to order a battery replacement through a platform and initiate delivery services. Traditional battery management systems lack a battery status assessment system during battery replacement and delivery. Platforms struggle to obtain timely and comprehensive real-time data on vehicle batteries, such as battery health status, actual range, and potential anomalies. After an order is placed, the delivery process often suffers from poor compatibility due to unclear battery information. The delivered new battery may not match the vehicle's actual needs, leading to wasted resources due to excessive range. Furthermore, changes in battery status during delivery are difficult to monitor; for example, battery anomalies caused by transportation vibrations or ambient temperature cannot be identified and addressed in advance. Consequently, platforms struggle to issue timely operational instructions to delivery personnel, and vehicle owners are unable to track service progress and battery status in real time, resulting in low collaborative efficiency. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a multi-role battery management method and service platform based on a service platform.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A multi-role battery management method based on a service platform, comprising the following steps:

[0006] A battery energy allocation system corresponding to the target new energy vehicle is obtained based on the actual driving range of the target new energy vehicle; the battery energy allocation system includes an allocation factor area, an abnormal allocation area, and an allocation result area; wherein, the allocation factor area includes a battery standard allocation factor and an allocation weight; the abnormal allocation area includes an abnormal allocation characteristic factor and an abnormal allocation diagnostic factor;

[0007] The vehicle's estimated range is obtained by processing and analyzing the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight, and actual driving range of the target new energy vehicle.

[0008] The abnormal monitoring and allocation factors are transmitted to the abnormal allocation area; the abnormal monitoring and allocation factors are matched and analyzed with the abnormal allocation feature factors to obtain the target abnormal allocation diagnostic factors corresponding to the target new energy vehicle; and the battery energy allocation status of the target new energy vehicle is obtained based on the target abnormal allocation diagnostic factors.

[0009] The vehicle's assessed driving range and battery energy allocation status are transmitted to the allocation results area, and the battery energy allocation results of the target new energy vehicle are obtained based on the allocation results area.

[0010] Preferably, the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight, and actual driving range of the target new energy vehicle are processed and analyzed to obtain the vehicle's assessed driving range. Specifically, this includes the following steps:

[0011] The battery monitoring and allocation factor of the target new energy vehicle is obtained based on the battery energy data of the target new energy vehicle.

[0012] The battery monitoring and allocation factors are input into the battery energy allocation system. The battery energy allocation system matches and analyzes the battery monitoring and allocation factors with the battery standard allocation factors to obtain the abnormal allocation factor parameters of the target new energy vehicle.

[0013] The abnormal impact range of the target new energy vehicle is obtained based on the allocation weight and abnormal allocation factor parameters, and the vehicle evaluation range of the target new energy vehicle is obtained based on the abnormal impact range and the actual range of the vehicle.

[0014] Preferably, the blending factor region includes a battery standard blending factor and a blending weight, specifically:

[0015] Obtain standard battery energy data for the target new energy vehicle based on its actual driving range.

[0016] Based on standard battery energy data, battery energy features are extracted to obtain the standard battery energy features corresponding to the target new energy vehicle.

[0017] Based on the standard battery energy characteristics, a standard battery allocation factor and a standard allocation parameter range corresponding to the target new energy vehicle are generated. The standard battery allocation factor corresponds to the standard battery energy characteristics.

[0018] The allocation weight of the standard battery allocation factor for the target new energy vehicle is set according to the actual driving range of the vehicle.

[0019] Preferably, the abnormal allocation zone includes abnormal allocation characteristic factors and abnormal allocation diagnostic factors, specifically:

[0020] Acquire historical battery energy anomaly data corresponding to the actual driving range of the vehicle, wherein the historical battery energy anomaly data includes battery energy anomaly monitoring data and battery energy diagnostic results;

[0021] Battery energy anomaly monitoring data is used to extract battery energy features to obtain the battery energy anomaly features corresponding to the target new energy vehicle; and anomaly allocation feature factors and anomaly allocation factor parameters are generated based on the battery energy anomaly features, wherein the anomaly allocation feature factors correspond to the battery energy anomaly features.

[0022] Battery energy diagnostic results are used to extract battery energy features to obtain the battery energy diagnostic features corresponding to the target new energy vehicle; and abnormal allocation diagnostic factors and diagnostic allocation factor parameters are generated based on the battery energy diagnostic features, wherein the abnormal allocation diagnostic factors correspond to the battery energy diagnostic features.

[0023] Preferably, the battery monitoring and allocation factor of the target new energy vehicle is obtained based on the battery energy data of the target new energy vehicle, including:

[0024] Battery energy features are extracted from battery energy data to obtain the battery monitoring energy features of the target new energy vehicle;

[0025] Based on the battery monitoring energy characteristics, a battery monitoring allocation factor and monitoring allocation factor parameters for the target new energy vehicle are generated, wherein the battery monitoring allocation factor corresponds to the battery monitoring energy characteristics.

[0026] Preferably, the battery energy allocation system performs matching analysis between battery monitoring allocation factors and standard battery allocation factors to obtain abnormal allocation factor parameters for the target new energy vehicle, including:

[0027] The battery monitoring allocation factor input into the battery energy allocation system is matched with the battery standard allocation factor to obtain the target standard allocation factor that is consistent with the battery monitoring allocation factor in the allocation factor region.

[0028] The monitoring and adjustment factor parameters of the battery monitoring and adjustment factor are compared with the standard adjustment parameter range of the target standard adjustment factor;

[0029] If the monitoring and adjustment factor parameter of the battery monitoring and adjustment factor is not within the standard adjustment parameter range of the target standard adjustment factor, then the battery monitoring and adjustment factor is recorded as the abnormal monitoring and adjustment factor, and the interval center parameter of the standard adjustment parameter range is obtained.

[0030] The abnormal allocation factor parameter of the abnormal monitoring allocation factor is obtained based on the interval center parameter and the monitoring allocation factor parameter.

[0031] Preferably, the abnormal impact range of the target new energy vehicle is obtained based on the allocation weight and abnormal allocation factor parameters, including:

[0032] The range impact coefficient of the target new energy vehicle is obtained by weighting and summing the abnormal allocation factor parameters and the allocation weight of the abnormal monitoring and allocation factor.

[0033] The abnormal impact range of the target new energy vehicle is obtained based on the range impact coefficient and the actual range of the vehicle.

[0034] Preferably, the abnormal allocation monitoring factor is matched and analyzed with the abnormal allocation characteristic factor to obtain the target abnormal allocation diagnostic factor corresponding to the target new energy vehicle, including:

[0035] The abnormal monitoring allocation factor is matched with the abnormal allocation feature factor in the abnormal allocation zone to obtain the abnormal monitoring allocation factor and the target allocation feature factor in the abnormal allocation zone.

[0036] Obtain the correlation between target allocation feature factors and target allocation factor, and obtain the target abnormal allocation diagnostic factor corresponding to the target allocation feature factor based on the correlation between target allocation factor and target allocation factor.

[0037] A multi-role battery management service platform based on a service platform, comprising:

[0038] Processing module: Based on the actual driving range of the target new energy vehicle, obtain the battery energy allocation system corresponding to the target new energy vehicle; the battery energy allocation system includes an allocation factor area, an abnormal allocation area, and an allocation result area; wherein, the allocation factor area includes battery standard allocation factors and allocation weights; the abnormal allocation area includes abnormal allocation characteristic factors and abnormal allocation diagnostic factors;

[0039] Analysis module: Processes and analyzes the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight and actual driving range of the target new energy vehicle to obtain the vehicle evaluation driving range of the target new energy vehicle.

[0040] Matching Analysis Module: Transmits the anomaly monitoring and allocation factors to the anomaly allocation area; performs matching analysis between the anomaly monitoring and allocation factors and the anomaly allocation feature factors to obtain the target anomaly allocation diagnostic factors corresponding to the target new energy vehicle; and obtains the battery energy allocation status of the target new energy vehicle based on the target anomaly allocation diagnostic factors.

[0041] Management module: Transmits the vehicle's assessed driving range and battery energy allocation status to the allocation results area, and obtains the battery energy allocation results of the target new energy vehicle based on the allocation results area.

[0042] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a multi-role battery management method and service platform based on a service platform.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] This invention generates appropriate battery standard matching factors, abnormal matching characteristics, and diagnostic factors based on the vehicle's actual driving range, allowing power replacement needs to be managed from the moment an order is placed. Before delivery, by matching the battery monitoring matching factors with the standard matching factors, abnormal battery status can be quickly identified, and the vehicle's range performance after power replacement can be predicted in advance. If abnormal battery matching factors are detected during delivery, they are matched with abnormal matching characteristic factors, and the connection trajectory is traced to obtain diagnostic factors, thereby clarifying the root cause of the battery abnormality. This application allows the user to know the estimated range after power replacement at the time of ordering, and to provide feedback and handle abnormal issues during delivery, and then understand the battery status after replacement, thus enabling vehicle owners to have full control over the dynamics of new energy vehicle battery swapping services. For example, the platform can push power matching suggestions and range guarantee plans to vehicle owners based on the battery energy matching results, improving the battery swapping service for new energy vehicles. Attached Figure Description

[0045] Figure 1 This invention provides a schematic diagram illustrating the steps of a multi-role battery management method based on a service platform.

[0046] Figure 2 This invention presents a schematic diagram of a multi-role battery management service platform based on a service platform.

[0047] Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention.

[0048] 610. Processor; 620. Communication interface; 630. Memory; 640. Communication bus. Detailed Implementation

[0049] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0050] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0052] like Figures 1 to 3 As shown.

[0053] Example 1 further illustrates the multi-role battery management method and service platform based on the service platform proposed in this invention.

[0054] A multi-role battery management method based on a service platform, comprising the following steps:

[0055] Based on the actual driving range of the target new energy vehicle, a battery energy allocation system corresponding to the target new energy vehicle is obtained; the battery energy allocation system includes an allocation factor area, an abnormal allocation area, and an allocation result area; among which, the allocation factor area includes battery standard allocation factors and allocation weights; the abnormal allocation area includes abnormal allocation characteristic factors and abnormal allocation diagnostic factors.

[0056] The vehicle's estimated range is obtained by processing and analyzing the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight, and actual driving range of the target new energy vehicle.

[0057] The abnormal monitoring and allocation factors are transmitted to the abnormal allocation area; the abnormal monitoring and allocation factors are matched and analyzed with the abnormal allocation feature factors to obtain the target abnormal allocation diagnostic factors corresponding to the target new energy vehicle; and the battery energy allocation status of the target new energy vehicle is obtained based on the target abnormal allocation diagnostic factors.

[0058] The vehicle's assessed driving range and battery energy allocation status are transmitted to the allocation results area, and the battery energy allocation results of the target new energy vehicle are obtained based on the allocation results area.

[0059] When a vehicle owner submits a request for a power supply replacement and places an order, the system first constructs a battery energy allocation system based on the actual driving range of the target new energy vehicle (this data relates to the driving distance supported by the vehicle's current remaining battery power, and also affects the range replenishment capability required by the power supply to be delivered). The battery energy allocation system is divided into an allocation factor area, an abnormal allocation area, and an allocation result area. In the allocation factor area, the standard battery allocation factor is set in conjunction with the vehicle model, power supply compatibility requirements, and delivery scenario. It covers the stable range that the voltage and current should maintain when the power supply is adapted to the vehicle, as well as ideal operating parameters such as charging and discharging efficiency. The allocation weight is assigned based on the degree to which different battery parameters affect the power supply compatibility effect and the vehicle's subsequent range. For example, the power capacity factor has a higher weight for vehicles with long range requirements, reflecting the priority of parameters for power supply compatibility. The abnormal allocation feature factors in the abnormal allocation area are derived from historical data such as battery failures and compatibility issues that occurred during past power supply distribution and replacement. Typical features include voltage surges after transport and signal anomalies caused by incompatibility with vehicle communication protocols. The abnormal allocation diagnostic factors are the root cause diagnoses of these anomalies, such as "micro-short circuit in power supply cells due to transport vibration" and "compatibility failure between power supply BMS and vehicle control system", providing a basis for identifying battery problems during distribution and replacement.

[0060] Collect battery energy data of target new energy vehicles (including current battery remaining capacity, voltage, current, health status, and energy consumption data under recent driving conditions). Extract features related to power supply replacement and adaptation from the battery energy data, such as the deviation between actual and theoretical range caused by battery aging. Compare this data with battery standard matching factors to identify deviations such as the current battery voltage being lower than the standard threshold for adapting to the new power supply and the impact of battery health status on the charging and discharging efficiency of the new power supply. Calculate the vehicle's estimated range by combining the actual driving range with a weighted calculation of the deviations. This range accurately reflects the actual driving distance the vehicle can achieve under expected operating conditions after replacing the power supply, allowing the platform, delivery personnel, and vehicle owners to know the range effect after the power supply replacement in advance. If the estimated range does not meet the requirements, adjust the power supply selection or delivery plan in a timely manner, such as replacing with a higher capacity power supply or optimizing delivery routes to reduce additional energy consumption.

[0061] During power supply delivery, the status of delivery vehicles and power supplies to be replaced is continuously monitored. If abnormal fluctuations in battery energy data are detected (such as voltage spikes or abnormal temperature increases due to road bumps during delivery, which may lead to power supply damage or incompatibility with vehicles), an abnormal monitoring and allocation factor is immediately generated and transmitted to the abnormal allocation zone. In the abnormal allocation zone, the abnormal monitoring and allocation factor is fully matched with pre-stored abnormal allocation feature factors to select the situation with the highest degree of fit with the abnormal battery data in the current delivery scenario. For example, if the abnormal monitoring factor shows characteristics such as voltage jumps, slow temperature rises, and unstable charging and discharging interface signals, it will be matched with the characteristic conditions of the power cell being damaged due to transportation vibration. Based on the matching results, the corresponding abnormal allocation diagnostic factors are retrieved to define the root cause of the abnormality and the level of impact on power supply delivery and replacement. The cause of the battery abnormality is located, and the battery energy allocation status, including the type of abnormality, the degree of impact on power supply replacement (such as the probability of failure when adapting to the vehicle), and potential risks (whether it will damage the vehicle's original circuit), is output. This allows platform operators and delivery personnel to quickly understand the severity of the problem and decide whether to continue delivery (taking protective measures, such as slowing down and reinforcing the power supply packaging) or return the abnormal power supply for replacement.

[0062] The vehicle's assessed driving range and battery energy allocation status are simultaneously transmitted to the allocation results area, becoming the basis for the final decision on power replacement delivery. The allocation results area generates battery energy allocation results adapted to the order scenario based on the core needs of the power replacement order (such as the vehicle urgently needing to resume operation and ensuring the new power supply is compatible and meets the driving range requirements) and preset rules (such as executing delivery and replacement when the assessed driving range can meet the vehicle's normal use for the next 3 days and the impact of abnormalities is controllable; if the abnormality may lead to a vehicle failure risk of more than 50%, the power replacement process is terminated and a new power supply is reissued). For delivery personnel, push notifications are sent such as "The current power supply, after assessment, can support a vehicle range of 300 kilometers, meeting the order requirements. Delivery will proceed along the original route," and "The power supply has a risk of battery cell damage; delivery must be immediately suspended and the power supply returned to the warehouse for replacement." For platform operations, strategies are provided such as "This order requires an expedited replacement of the power supply due to an abnormality; delivery resources will be adjusted to prioritize this task," and "Based on the assessed range, usage suggestions after the power supply replacement are sent to the vehicle owner (such as avoiding immediate long-distance driving)." For vehicle owners, notifications are sent such as "The replacement power supply you ordered is expected to provide a range of 300 kilometers after adaptation; please check for delivery during the delivery process," and "Due to an abnormality in the delivered power supply, the new power supply will be delivered 6 hours late; a higher capacity power supply will be provided to ensure your continued use." By employing a multi-role collaborative strategy involving delivery personnel, platform operators, and vehicle owners, we ensure controllable response to battery status anomalies during the new energy vehicle power replacement delivery service. This guarantees smooth power replacement and vehicle resumption of operation while maintaining battery health and vehicle safety. We achieve closed-loop management throughout the entire process, from battery allocation planning at order initiation to handling anomalies during delivery and optimizing feedback. This integrates battery management into the new energy vehicle power replacement delivery business, improving service efficiency and user satisfaction.

[0063] The target new energy vehicle's estimated driving range is obtained by processing and analyzing its battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight, and actual driving range. This process includes the following steps:

[0064] The battery monitoring and allocation factor of the target new energy vehicle is obtained based on the battery energy data of the target new energy vehicle.

[0065] The battery monitoring and allocation factors are input into the battery energy allocation system. The battery energy allocation system matches and analyzes the battery monitoring and allocation factors with the battery standard allocation factors to obtain the abnormal allocation factor parameters of the target new energy vehicle.

[0066] The abnormal impact range of the target new energy vehicle is obtained based on the allocation weight and abnormal allocation factor parameters, and the vehicle evaluation range of the target new energy vehicle is obtained based on the abnormal impact range and the actual range of the vehicle.

[0067] Obtain real-time, multi-dimensional battery energy data from the target new energy vehicle, including the battery's current voltage, current, remaining charge, state of health (SOH), and recent charge and discharge records under different operating conditions.

[0068] The generated battery monitoring and allocation factors are input into a pre-built battery energy allocation system based on the vehicle's actual driving range. Within this system, the battery monitoring and allocation factors are matched with pre-set standard battery allocation factors. These standard factors include vehicle model, compatible power supply specifications, operating parameters of high-quality industry batteries, and characteristic parameters that a battery should possess under ideal conditions, such as the stable voltage range that a specific vehicle model should maintain under standard operating conditions and the reasonable range of charge and discharge efficiency. By comparing the two, the differences between the battery monitoring and allocation factors and the standard factors are identified, thus obtaining abnormal allocation factor parameters for the target new energy vehicle. These parameters quantify the degree of deviation of the current battery state from the ideal state, such as the extent to which the voltage exceeds the standard range and the difference between the charge decay rate and the standard value, defining abnormal battery performance in delivery service-related scenarios.

[0069] The impact of abnormal allocation factors on driving range is calculated by combining allocation weights with battery parameters. Allocation weights are set based on the actual importance of different battery parameters to vehicle driving range. For example, in a power swap delivery scenario, the allocation weight for battery capacity-related parameters will be higher if the vehicle needs to handle long-distance driving. The abnormal impact on driving range is obtained by weighting the abnormal allocation factors with their corresponding allocation weights. Delivery personnel can then rationally plan delivery routes to ensure both efficient service and continued normal vehicle use. From battery data processing to driving range assessment, this facilitates the delivery of power swap services for new energy vehicles.

[0070] The blending factor region includes the battery standard blending factor and blending weight, specifically:

[0071] Obtain standard battery energy data for the target new energy vehicle based on its actual driving range.

[0072] Based on standard battery energy data, battery energy features are extracted to obtain the standard battery energy features corresponding to the target new energy vehicle.

[0073] Based on the standard battery energy characteristics, the standard battery allocation factor and standard allocation parameter range corresponding to the target new energy vehicle are generated, and the standard battery allocation factor corresponds to the standard battery energy characteristics.

[0074] The allocation weight of the standard battery allocation factor for the target new energy vehicle is set according to the actual driving range of the vehicle.

[0075] In the scenario where new energy vehicles place orders for power replacements and receive delivery services through a platform, the construction of battery standard allocation factors and allocation weights is fundamental to battery management and ensuring service quality. When a vehicle submits a power replacement request, the standard battery energy data of the target new energy vehicle is first obtained based on its actual driving range. The actual driving range reflects the vehicle's current and past energy consumption levels and battery performance. The standard battery energy data obtained based on this data facilitates the acquisition of ideal battery operating data that closely matches the vehicle's real-world usage scenarios, including the reasonable state that key parameters such as battery voltage, current, capacity, and charge / discharge efficiency should be under the corresponding driving range performance.

[0076] Next, battery energy feature extraction is performed. Features that represent the ideal working state of the battery are extracted from the data to form standard battery energy features corresponding to the target new energy vehicle. For example, the voltage stability range and current fluctuation pattern of the battery at different stages (such as start-up, constant speed driving, and regenerative braking) are identified during the process of achieving the actual driving range of the vehicle.

[0077] Based on the extracted standard battery energy characteristics, standard battery matching factors and standard matching parameter ranges are generated. The standard matching parameter range indicates the reasonable fluctuation range of each factor. For example, the parameter range corresponding to the standard battery voltage factor of a certain model is 3.2V-3.8V, providing a clear quantitative basis for judging whether the battery status is normal.

[0078] The allocation weights of corresponding battery standard allocation factors are set based on the vehicle's actual driving range. The weights of each battery parameter's impact on range vary depending on the actual driving range. If the actual driving range is long, the allocation weights are adjusted to match the vehicle's usage needs reflected by the actual driving range. This facilitates data processing and decision-making during subsequent power replacement and delivery services, based on the degree of influence of each factor on battery management and vehicle usage.

[0079] The battery standard matching factor and matching weight are constructed in the entire power replacement and delivery service process. When judging the suitability of power replacement, the standard matching factor is compared with the actual monitored battery matching factor to identify anomalies and deviations. The matching weight is used in the process of calculating the impact of anomalies on range and formulating power replacement strategies (such as whether a higher capacity power supply is needed, and which battery parameters should be prioritized), and assigning reasonable influence weights to different battery parameters to facilitate the power replacement and delivery service for new energy vehicles.

[0080] The abnormal allocation zone includes abnormal allocation characteristic factors and abnormal allocation diagnostic factors, specifically:

[0081] Obtain historical battery energy anomaly data corresponding to the actual driving range of the vehicle. The historical battery energy anomaly data includes battery energy anomaly monitoring data and battery energy diagnostic results.

[0082] Battery energy anomaly monitoring data is used to extract battery energy features to obtain the battery energy anomaly features corresponding to the target new energy vehicle; and based on the battery energy anomaly features, anomaly allocation feature factors and anomaly allocation factor parameters are generated, with the anomaly allocation feature factors corresponding to the battery energy anomaly features.

[0083] Battery energy diagnostic results are used to extract battery energy features to obtain the battery energy diagnostic features corresponding to the target new energy vehicle; and abnormal allocation diagnostic factors and diagnostic allocation factor parameters are generated based on the battery energy diagnostic features, with the abnormal allocation diagnostic factors corresponding to the battery energy diagnostic features.

[0084] In this application, the construction of an anomaly dispatch zone is a crucial step in ensuring smooth service when new energy vehicles place orders for power replacements on the platform and initiate delivery services. When a vehicle initiates a power replacement request, the application first focuses on the vehicle's actual driving range, using this as a guide to collect corresponding historical battery energy anomaly data. This includes battery energy anomaly monitoring data (such as sudden voltage jumps, abnormal temperature increases, and sharp drops in charging and discharging efficiency, etc., which are real-time monitored anomalies) and battery energy diagnostic results (i.e., the root causes of these anomalies previously identified, such as cell consistency imbalance and BMS communication failures).

[0085] Battery energy anomaly monitoring data is used to extract battery energy features. Key features representing abnormal battery states are identified from the anomaly monitoring data to form the corresponding battery energy anomaly characteristics for the target new energy vehicle. For example, from anomaly monitoring data of a sudden drop in range due to battery overheating, features such as "temperature rises by more than 10°C in a short period of time, while voltage continues to drop" are extracted. Based on these anomaly features, anomaly allocation feature factors and anomaly allocation factor parameters are generated; the anomaly allocation factor parameters quantify the degree and scope of the anomaly, such as the range loss value corresponding to the temperature rise.

[0086] Battery energy feature extraction is performed on the battery energy diagnostic results. Underlying battery state characteristics are extracted from diagnostic conclusions (such as "micro-short circuit in the cell causes abnormal battery performance") to form battery energy diagnostic features corresponding to the target new energy vehicle, clarifying the root cause of the fault at the battery data level. Based on these diagnostic features, abnormal allocation diagnostic factors and diagnostic allocation factor parameters are generated. Abnormal allocation diagnostic factors and battery energy diagnostic features are in one-to-one correspondence; when a corresponding abnormal allocation feature factor is matched, it is associated with that diagnostic factor. The diagnostic allocation factor parameters provide a quantitative description of the fault's impact and repair difficulty, helping to determine the degree of interference of the abnormality on the power replacement and delivery service.

[0087] In the power supply replacement and delivery service process, when anomalies are detected in the vehicle's battery data (such as fluctuations in battery parameters caused by vibrations during delivery), an anomaly monitoring and allocation factor is generated and enters the anomaly allocation zone. At this point, the anomaly monitoring and allocation factor is first matched with anomaly allocation characteristic factors. If a match is successful, the root cause of the battery anomaly is located through associated anomaly allocation diagnostic factors, identifying a voltage anomaly caused by cell displacement during transportation. Based on this, adjustments can be made, such as adjusting the delivery plan (changing delivery vehicles, reinforcing power supply packaging), preparing contingency plans in advance, or replacing the power supply with a compatible one.

[0088] Based on the battery energy data of the target new energy vehicle, the battery monitoring and allocation factors of the target new energy vehicle are obtained, including:

[0089] Battery energy features are extracted from battery energy data to obtain the battery monitoring energy features of the target new energy vehicle;

[0090] Based on the energy characteristics of battery monitoring, the system generates battery monitoring allocation factors and monitoring allocation factor parameters for the target new energy vehicle. The battery monitoring allocation factors correspond to the energy characteristics of battery monitoring.

[0091] In scenarios where new energy vehicles place orders for power replacements and receive delivery services through a platform, obtaining battery monitoring and adjustment factors is crucial for understanding the current state of the battery and providing a basis for subsequent service decisions. When a vehicle submits a power replacement request, battery energy data of the target new energy vehicle is collected. This data covers multiple dimensions of information, including real-time battery voltage, current, remaining charge, temperature, state of health (SOH), and recent charge / discharge history.

[0092] Battery energy features are extracted from these battery energy data. Key features that represent the current operating state of the battery are screened and refined to form the battery monitoring energy features of the target new energy vehicle. For example, features such as voltage fluctuation patterns (whether they are stable fluctuations or abnormal jumps), charge decay trends (whether they are faster than before), and temperature change patterns (whether they are within the normal range) are identified during the current usage cycle.

[0093] Based on the extracted battery monitoring energy characteristics, battery monitoring allocation factors and monitoring allocation factor parameters are generated. The battery monitoring allocation factor is a standardized and structured representation of the battery monitoring energy characteristics. For example, if the battery monitoring energy characteristic is "the voltage experiences three jumps exceeding the normal fluctuation range within a short period of time," the corresponding battery monitoring allocation factor describes this characteristic. The monitoring allocation factor parameters are a quantitative supplement to this characteristic, providing data such as the amplitude of the voltage jumps and the duration of each jump, allowing for precise measurement of the abnormal or normal performance of the battery's current state.

[0094] During the delivery service, battery energy data is acquired and updated, continuously generating new battery monitoring and adjustment factors. By comparing these factors with standard battery adjustment factors, it is possible to promptly detect whether the battery condition deviates from the ideal value and to determine whether any abnormalities occur during the power swap delivery process (such as abnormal voltage fluctuations due to transportation vibrations). Potential problems can be warned in advance, allowing for adjustments to delivery strategies (such as optimizing transportation routes to reduce the impact of bumps on the battery) or the preparation of suitable backup power supplies. This ensures that the power swap delivery service is both efficient and maintains good battery condition, laying a solid foundation for the subsequent normal use of the vehicle. From in-depth mining of battery data to dynamic adjustment of service strategies, a battery management system adapted to the power swap delivery scenario for new energy vehicles is constructed.

[0095] The battery energy allocation system matches and analyzes battery monitoring allocation factors with standard battery allocation factors to obtain abnormal allocation factor parameters for the target new energy vehicle, including:

[0096] The battery monitoring allocation factor input into the battery energy allocation system is matched with the battery standard allocation factor to obtain the target standard allocation factor that is consistent with the battery monitoring allocation factor in the allocation factor region.

[0097] The monitoring and adjustment factor parameters of the battery monitoring and adjustment factor are compared with the standard adjustment parameter range of the target standard adjustment factor;

[0098] If the monitoring and adjustment factor parameter of the battery monitoring and adjustment factor is not within the standard adjustment parameter range of the target standard adjustment factor, then the battery monitoring and adjustment factor is recorded as the abnormal monitoring and adjustment factor, and the interval center parameter of the standard adjustment parameter range is obtained.

[0099] The abnormal allocation factor parameters of the abnormal monitoring and allocation factors are obtained based on the interval center parameters and the monitoring and allocation factor parameters.

[0100] In scenarios where new energy vehicles place orders for power replacement on the platform and delivery services are carried out, the battery energy allocation system performs matching analysis between battery monitoring allocation factors and battery standard allocation factors to facilitate the identification of battery status and ensure service quality. When a vehicle submits a power replacement request and battery monitoring allocation factors (characteristic presentation of the current battery status) have been generated, these factors will be input into the battery energy allocation system to start the matching analysis process.

[0101] The input battery monitoring and matching factors are matched with the standard battery matching factors. The standard battery matching factors are pre-set based on ideal vehicle conditions and past high-quality data, representing the characteristics of a battery operating normally and efficiently. The matching process identifies a target standard matching factor from the matching factor range that matches the battery monitoring and matching factors.

[0102] The monitoring and adjustment factor parameters of the battery monitoring and adjustment factors are compared with the standard adjustment parameter range of the target standard adjustment factor. The standard adjustment parameter range defines the numerical range of the corresponding factor during normal operation. For example, the standard parameter range of a certain battery voltage factor is 3.2V-3.8V.

[0103] If the monitoring and adjustment factor parameter of the battery monitoring and adjustment factor is not within the standard adjustment parameter range, it indicates that the current state of the battery is abnormal. In this case, the battery monitoring and adjustment factor is recorded as the abnormal monitoring and adjustment factor. At the same time, the center parameter of the standard adjustment parameter range is obtained.

[0104] Finally, based on the interval center parameter and the monitoring and adjustment factor parameter, the abnormal adjustment factor parameter of the abnormal monitoring and adjustment factor is calculated. By calculating and quantifying the deviation of the current state of the battery from the ideal state, such as the voltage factor monitoring parameter being 3.0V and the center parameter being 3.5V, the deviation degree and other data are calculated.

[0105] If battery parameters become abnormal during delivery due to factors such as road bumps, the above process identifies the anomalies in the battery monitoring and adjustment factors. Based on the abnormal adjustment factor parameters, the impact of the anomaly on vehicle use after power replacement is assessed. If the anomaly is minor, the delivery plan can be adjusted (e.g., slowing down to reduce further impact) and delivery can continue. If the anomaly is severe, strategies such as timely replacement of the backup power supply, delivery suspension, and repair are promptly triggered to ensure that the battery status remains controllable throughout the power replacement delivery service for new energy vehicles. This avoids the impact of using abnormal batteries on subsequent vehicle operation and efficiently responds to unexpected battery situations during delivery.

[0106] The abnormal impact range of the target new energy vehicle is obtained based on the allocation weight and abnormal allocation factor parameters, including:

[0107] The range impact coefficient of the target new energy vehicle is obtained by weighting and summing the abnormal allocation factor parameters and the allocation weight of the abnormal monitoring and allocation factor.

[0108] The abnormal impact range of the target new energy vehicle is obtained based on the range impact coefficient and the actual range of the vehicle.

[0109] This application addresses the critical role of calculating the impact of abnormalities on driving range in scenarios where new energy vehicles order power replacements and receive delivery services through a platform. It assesses the impact of battery status on subsequent vehicle use and ensures service quality. Once the abnormal monitoring and allocation factors are identified through the battery energy allocation system and their parameters are obtained, the calculation process for the impact of abnormalities on driving range begins.

[0110] Each anomaly monitoring and allocation factor has a corresponding allocation weight, which is set based on the actual importance of the factor's impact on vehicle range. In power swapping and delivery scenarios, different battery anomaly factors have varying impacts on the vehicle's subsequent range. For example, if a battery voltage anomaly factor directly leads to a significant decrease in charging and discharging efficiency, its allocation weight will be relatively high.

[0111] The abnormal allocation factor parameter of the abnormal monitoring and allocation factor is weighted and accumulated with the allocation weight of the factor. The abnormal allocation factor parameter quantifies the degree of battery abnormality, and the allocation weight reflects the weight of the abnormality's impact on the range. The weighted sum of the two yields the range impact coefficient of the target new energy vehicle.

[0112] The abnormal impact range is calculated based on the range impact coefficient and the vehicle's actual driving range. The actual driving range is the known baseline data. Multiplying the actual driving range by the range impact coefficient yields the range loss caused by the battery malfunction, which is the abnormal impact range.

[0113] If the battery anomaly significantly impacts the driving range beyond the vehicle's subsequent usage needs, a higher-quality power supply and an adjustment to the power supply specifications used during delivery are required. Delivery personnel can also be aware of the impact of the battery anomaly on the vehicle in advance and take protective measures during delivery to prevent the anomaly from escalating. Vehicle owners can understand the vehicle's actual driving range after the power supply replacement and plan their subsequent trips accordingly. From battery anomaly identification to quantifying the anomaly's impact on driving range, and then to adjusting service strategies, this process provides data support for new energy vehicle power supply replacement and delivery services.

[0114] The abnormal allocation diagnostic factors for the target new energy vehicle are obtained by matching and analyzing the abnormal allocation monitoring factors with the abnormal allocation characteristic factors, including:

[0115] The abnormal monitoring allocation factor is matched with the abnormal allocation feature factor in the abnormal allocation zone to obtain the abnormal monitoring allocation factor and the target allocation feature factor in the abnormal allocation zone.

[0116] Obtain the correlation between target allocation feature factors and target allocation factor, and obtain the target abnormal allocation diagnostic factor corresponding to the target allocation feature factor based on the correlation between target allocation factor and target allocation factor.

[0117] In the scenario where new energy vehicles place orders for power replacement on the platform and the delivery service is carried out, the matching of abnormal monitoring and allocation factors with abnormal allocation characteristic factors is the key to locating the root cause of battery abnormalities and ensuring the smooth operation of the service.

[0118] First, the anomaly monitoring and allocation factors are matched with the anomaly allocation feature factors in the anomaly allocation zone. The anomaly allocation feature factors are a set of features extracted from a large amount of historical battery anomaly data, representing typical states of various battery anomalies, covering feature templates when batteries exhibit anomalies due to different reasons (such as cell short circuits, BMS communication failures, temperature runaway, etc.). The service platform compares the anomaly monitoring and allocation factors to select target allocation feature factors from the anomaly allocation zone that correspond to the current battery anomaly state.

[0119] There is a correlation between abnormal matching characteristic factors and specific abnormal matching diagnostic factors. Based on the correlation of target matching factors, the target abnormal matching diagnostic factors corresponding to the target matching characteristic factors are obtained. By tracing the correlation, the diagnostic conclusions corresponding to the current abnormal characteristic factors can be found from historical correlations, clarifying the specific root cause of battery abnormalities, such as aging damage to battery cells due to long-term charging and discharging, or structural abnormalities caused by vibration during power supply distribution and transportation.

[0120] Assuming an anomaly monitoring factor ("abnormal voltage fluctuations in the battery") is detected during delivery, it is matched with other anomaly adjustment characteristic factors to find the corresponding characteristic factor ("cell displacement due to transportation vibration"). Then, based on their correlation, the anomaly adjustment diagnostic factor ("micro-short circuit risk in the cell") is obtained. If the anomaly is minor, the delivery plan can be adjusted (e.g., choosing a smoother route) and the power supply can be simply reinforced. If the anomaly is severe, the backup power supply is immediately replaced to avoid delivering a potentially unsafe power supply to the vehicle owner, ensuring the vehicle's subsequent safety. Simultaneously, delivery personnel can take measures to mitigate the impact of the anomaly based on the diagnostic results; and after receiving the power supply replacement service, the vehicle owner understands the root cause of the battery anomaly, facilitating subsequent maintenance.

[0121] Example 2: A multi-role battery management service platform based on a service platform, comprising:

[0122] Processing module: Based on the actual driving range of the target new energy vehicle, the battery energy allocation system corresponding to the target new energy vehicle is obtained; the battery energy allocation system includes allocation factor area, abnormal allocation area and allocation result area; among which, the allocation factor area includes battery standard allocation factor and allocation weight; the abnormal allocation area includes abnormal allocation characteristic factor and abnormal allocation diagnostic factor.

[0123] Analysis module: Processes and analyzes the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight and actual driving range of the target new energy vehicle to obtain the vehicle evaluation driving range of the target new energy vehicle.

[0124] Matching Analysis Module: Transmits the anomaly monitoring and allocation factors to the anomaly allocation area; performs matching analysis between the anomaly monitoring and allocation factors and the anomaly allocation feature factors to obtain the target anomaly allocation diagnostic factors corresponding to the target new energy vehicle; and obtains the battery energy allocation status of the target new energy vehicle based on the target anomaly allocation diagnostic factors.

[0125] Management module: Transmits the vehicle's assessed driving range and battery energy allocation status to the allocation results area, and obtains the battery energy allocation results of the target new energy vehicle based on the allocation results area.

[0126] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a multi-role battery management method and service platform based on a service platform.

[0127] like Figure 3 As shown, the electronic device may include a processor 610, a communication interface 620, a memory 630, and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other through the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute a multi-role battery management method based on a service platform.

[0128] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0129] On the other hand, the present invention also provides a computer program product, the computer program product including a computer program that can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer is able to execute a multi-role battery management method based on a service platform.

[0130] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform a multi-role battery management method based on a service platform.

[0131] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0132] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-role battery management method based on a service platform, characterized in that, The method includes the following steps: A battery energy allocation system corresponding to the target new energy vehicle is obtained based on the actual driving range of the target new energy vehicle; the battery energy allocation system includes an allocation factor area, an abnormal allocation area, and an allocation result area; wherein, the allocation factor area includes a battery standard allocation factor and an allocation weight; the abnormal allocation area includes an abnormal allocation characteristic factor and an abnormal allocation diagnostic factor; The vehicle's estimated range is obtained by processing and analyzing the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight, and actual driving range of the target new energy vehicle. The abnormal monitoring and allocation factors are transmitted to the abnormal allocation area; the abnormal monitoring and allocation factors are matched and analyzed with the abnormal allocation feature factors to obtain the target abnormal allocation diagnostic factors corresponding to the target new energy vehicle; and the battery energy allocation status of the target new energy vehicle is obtained based on the target abnormal allocation diagnostic factors. The vehicle's assessed driving range and battery energy allocation status are transmitted to the allocation results area, and the battery energy allocation results of the target new energy vehicle are obtained based on the allocation results area.

2. The multi-role battery management method based on a service platform according to claim 1, characterized in that, The target new energy vehicle's estimated driving range is obtained by processing and analyzing its battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight, and actual driving range. This process includes the following steps: The battery monitoring and allocation factor of the target new energy vehicle is obtained based on the battery energy data of the target new energy vehicle. The battery monitoring and allocation factors are input into the battery energy allocation system. The battery energy allocation system matches and analyzes the battery monitoring and allocation factors with the battery standard allocation factors to obtain the abnormal allocation factor parameters of the target new energy vehicle. The abnormal impact range of the target new energy vehicle is obtained based on the allocation weight and abnormal allocation factor parameters, and the vehicle evaluation range of the target new energy vehicle is obtained based on the abnormal impact range and the actual range of the vehicle.

3. The multi-role battery management method based on a service platform according to claim 2, characterized in that, The matching factor region includes the battery standard matching factor and matching weight, specifically: Obtain standard battery energy data for the target new energy vehicle based on its actual driving range. Based on standard battery energy data, battery energy features are extracted to obtain the standard battery energy features corresponding to the target new energy vehicle. Based on the standard battery energy characteristics, a standard battery allocation factor and a standard allocation parameter range corresponding to the target new energy vehicle are generated. The standard battery allocation factor corresponds to the standard battery energy characteristics. The allocation weight of the standard battery allocation factor for the target new energy vehicle is set according to the actual driving range of the vehicle.

4. The multi-role battery management method based on a service platform according to claim 3, characterized in that, The abnormal allocation region includes abnormal allocation characteristic factors and abnormal allocation diagnostic factors, specifically: Acquire historical battery energy anomaly data corresponding to the actual driving range of the vehicle, wherein the historical battery energy anomaly data includes battery energy anomaly monitoring data and battery energy diagnostic results; Battery energy anomaly monitoring data is used to extract battery energy features to obtain the battery energy anomaly features corresponding to the target new energy vehicle. Based on the abnormal characteristics of battery energy, abnormal allocation characteristic factors and abnormal allocation factor parameters are generated, wherein the abnormal allocation characteristic factors correspond to the abnormal characteristics of battery energy. Battery energy diagnostic results are used to extract battery energy features to obtain the battery energy diagnostic features corresponding to the target new energy vehicle; and abnormal allocation diagnostic factors and diagnostic allocation factor parameters are generated based on the battery energy diagnostic features, wherein the abnormal allocation diagnostic factors correspond to the battery energy diagnostic features.

5. A multi-role battery management method based on a service platform according to claim 4, characterized in that, Based on the battery energy data of the target new energy vehicle, the battery monitoring and allocation factors of the target new energy vehicle are obtained, including: Battery energy features are extracted from battery energy data to obtain the battery monitoring energy features of the target new energy vehicle; Based on the battery monitoring energy characteristics, a battery monitoring allocation factor and monitoring allocation factor parameters for the target new energy vehicle are generated, wherein the battery monitoring allocation factor corresponds to the battery monitoring energy characteristics.

6. The multi-role battery management method based on a service platform according to claim 5, characterized in that, The battery energy allocation system matches and analyzes battery monitoring allocation factors with standard battery allocation factors to obtain abnormal allocation factor parameters for the target new energy vehicle, including: The battery monitoring allocation factor input into the battery energy allocation system is matched with the battery standard allocation factor to obtain the target standard allocation factor that is consistent with the battery monitoring allocation factor in the allocation factor region. The monitoring and adjustment factor parameters of the battery monitoring and adjustment factor are compared with the standard adjustment parameter range of the target standard adjustment factor; If the monitoring and adjustment factor parameter of the battery monitoring and adjustment factor is not within the standard adjustment parameter range of the target standard adjustment factor, then the battery monitoring and adjustment factor is recorded as the abnormal monitoring and adjustment factor, and the interval center parameter of the standard adjustment parameter range is obtained. The abnormal allocation factor parameter of the abnormal monitoring allocation factor is obtained based on the interval center parameter and the monitoring allocation factor parameter.

7. A multi-role battery management method based on a service platform according to claim 6, characterized in that, The abnormal impact range of the target new energy vehicle is obtained based on the allocation weight and abnormal allocation factor parameters, including: The range impact coefficient of the target new energy vehicle is obtained by weighting and summing the abnormal allocation factor parameters and the allocation weight of the abnormal monitoring and allocation factor. The abnormal impact range of the target new energy vehicle is obtained based on the range impact coefficient and the actual range of the vehicle.

8. A multi-role battery management method based on a service platform according to claim 7, characterized in that, The abnormal allocation diagnostic factors for the target new energy vehicle are obtained by matching and analyzing the abnormal allocation monitoring factors with the abnormal allocation characteristic factors, including: The abnormal monitoring allocation factor is matched with the abnormal allocation feature factor in the abnormal allocation zone to obtain the target allocation feature factor in the abnormal allocation zone that matches the abnormal monitoring allocation factor. Obtain the correlation between target allocation feature factors and target allocation factor, and obtain the target abnormal allocation diagnostic factor corresponding to the target allocation feature factor based on the correlation between target allocation factor and target allocation factor.

9. A multi-role battery management service platform based on a service platform, applied to the multi-role battery management method based on a service platform as described in any one of claims 1 to 8, characterized in that, include: Processing module: Based on the actual driving range of the target new energy vehicle, obtain the battery energy allocation system corresponding to the target new energy vehicle; the battery energy allocation system includes an allocation factor area, an abnormal allocation area, and an allocation result area; wherein, the allocation factor area includes battery standard allocation factors and allocation weights; the abnormal allocation area includes abnormal allocation characteristic factors and abnormal allocation diagnostic factors; Analysis module: Processes and analyzes the battery energy data, battery energy allocation system, battery standard allocation factor, allocation weight and actual driving range of the target new energy vehicle to obtain the vehicle evaluation driving range of the target new energy vehicle. Matching Analysis Module: Transmits the anomaly monitoring and allocation factors to the anomaly allocation area; performs matching analysis between the anomaly monitoring and allocation factors and the anomaly allocation feature factors to obtain the target anomaly allocation diagnostic factors corresponding to the target new energy vehicle; and obtains the battery energy allocation status of the target new energy vehicle based on the target anomaly allocation diagnostic factors. Management module: Transmits the vehicle's assessed driving range and battery energy allocation status to the allocation results area, and obtains the battery energy allocation results of the target new energy vehicle based on the allocation results area.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements a multi-role battery management method based on a service platform as described in any one of claims 1 to 8.

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