A new energy vehicle circulating power supply method based on double battery pack alternate power supply

Abstract

This invention discloses a method for cyclic power supply of new energy vehicles based on alternating dual-battery pack power supply, relating to the field of new energy vehicle technology. The key technical solutions include the following specific steps: collecting equipment status data information of the vehicle's electrical circuits and integrated cyclic power generation control commands for the vehicle's three-electric system; the equipment status data information includes a dual-battery pack status dataset, a dual-power switching trigger condition dataset, and a set of coaxial power generation charging and discharging linkage execution parameters; obtaining the linkage cyclic power supply characteristics of the target power supply battery pack, the dual-battery pack coaxial DC motor, and the AC generator in the integrated cyclic power generation control commands for the vehicle's three-electric system; the effect is that it can distinguish the task execution order according to the weights of driving safety, battery protection, and vehicle energy efficiency, dynamically allocate the output load of the two battery packs, avoid a single battery pack continuously bearing large current impacts for a long time, slow down the battery degradation rate, and extend the service life of the power battery.

Description

Technical Field

[0001] This invention relates to the field of new energy vehicle technology, and more specifically, to a method for cyclic power supply of new energy vehicles based on alternating power supply from dual battery packs. Background Technology

[0002] New energy vehicles rely on stacking large-capacity battery packs to improve range. The total weight of batteries in conventional models can reach over 400 kg, and the standard operating range can only cover 350 to 800 km. The industry has long suffered from two core pain points: insufficient range and inconvenient charging. Due to the physical limitations of lithium battery energy density, automakers generally extend the driving range by increasing the number of battery modules. However, stacking a large number of battery packs will significantly occupy the chassis loading space, squeeze the passenger and storage areas, and continuously increase the vehicle's weight. Energy consumption during driving will also increase simultaneously, forming a vicious cycle of increased weight and energy consumption, which in turn increases the weight of the battery. At the same time, the procurement cost of power batteries remains high, making it difficult to reduce the vehicle price and the cost of replacement later.

[0003] Furthermore, existing simple dual-battery switching solutions only include basic on / off switches and lack a complete three-electric coordinated control system. They lack hierarchical power supply task determination, switching sequence evaluation, and operational reliability verification throughout the entire control process. This results in slow power switching response, voltage and current surges during switching, and the inability of the coaxial DC motor and AC generator to synchronize and match, hindering continuous cyclic power generation. The millisecond-level switching delay of conventional switching devices causes short-term power interruptions, affecting driving smoothness. The lack of standardized linkage constraints between motor torque and generator output power easily leads to situations where motor power consumption exceeds power generation revenue, resulting in low energy utilization efficiency. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a new energy vehicle cyclic power supply method based on alternating power supply of dual battery packs.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for cyclic power supply of new energy vehicles based on alternating power supply from dual battery packs, the method comprising the following specific steps:

[0007] Collects equipment status data information of the vehicle's electrical circuits and control commands for the integrated cycle power generation of the vehicle's three electric systems; the equipment status data information includes dual battery pack status datasets, dual power supply switching trigger condition datasets, and coaxial power generation charging and discharging linkage execution parameter sets;

[0008] The linkage and cyclic power supply characteristics of the target power supply battery pack, the coaxial DC motor and AC generator of the dual battery pack are obtained in the integrated cyclic power generation control command of the vehicle's three electric systems.

[0009] Prioritize and classify the characteristics of the linked cyclic power supply to obtain the result set of the linked cyclic power supply task, and generate a set of linked cyclic power supply tasks to be executed based on the result set of the linked cyclic power supply task.

[0010] Based on the key dual-power automatic switching trigger nodes, vehicle electrical circuit equipment status data, and electrical interaction data between the dual battery packs and the coaxial generator set, a power switching timing evaluation set to be processed is generated from the results of the cyclic power supply linkage task.

[0011] Obtain the coaxial power generation charging and discharging linkage execution records of key dual power supply automatic switching trigger nodes, and generate a set of reliability assessment results for the cyclic power supply to be executed by combining the dual power supply switching trigger condition dataset;

[0012] By integrating the set of pending cyclic power supply linkage tasks, the set of pending power supply switching timing evaluations, and the set of pending cyclic power supply reliability evaluation results, a cyclic power supply execution scheme for alternating power supply from dual battery packs and coaxial motor generators is obtained.

[0013] Preferably, the priority classification of the linked cyclic power supply characteristics is used to obtain a cyclic power supply linkage task result set, and a set of cyclic power supply linkage tasks to be executed is generated based on the cyclic power supply linkage task result set, specifically including the following steps:

[0014] Priority classification is performed on the characteristics of the linked cyclic power supply to obtain the cyclic power supply linkage task. The cyclic power supply linkage task is then decomposed into a hierarchical structure to obtain the cyclic power supply linkage task result set.

[0015] Collect the electrical hardware information of the target power supply battery pack and identify the high-voltage electrical circuits of the vehicle to obtain the electrical circuit identification results;

[0016] Based on the electrical circuit identification results and the characteristics of the linked cyclic power supply, electrical circuit adaptation processing is performed on each level of the cyclic power supply linkage task result set to generate a set of cyclic power supply linkage tasks to be executed.

[0017] Preferably, based on the key dual-power automatic switching trigger nodes, vehicle electrical circuit equipment status data, and electrical interaction data between the dual battery packs and the coaxial generator set in the result set of the cyclic power supply linkage task, a power supply switching timing evaluation set to be processed is generated, specifically including the following steps:

[0018] Extract key dual-power automatic switching trigger nodes from the results of the cyclic power supply linkage task;

[0019] Based on the key dual-power automatic switching trigger node, the alternating power supply switching conditions of the dual battery packs are preset. According to the matching degree between the alternating power supply switching conditions of the dual battery packs and the dual battery pack status dataset, and the power transmission delay data from the dual battery packs to the coaxial generator set, the first electrical interaction performance dataset is generated.

[0020] A second electrical interaction performance dataset is generated based on the matching degree between the alternating power supply switching conditions of the dual battery packs and the dual battery pack state dataset, as well as the synchronization deviation data of the dual battery pack output voltage.

[0021] By combining the first electrical interaction performance dataset, the second electrical interaction performance dataset, the dual battery pack status dataset, and the coaxial power generation charging and discharging linkage execution parameter set, a comprehensive evaluation of the switching timing of the dual battery pack coaxial integrated power generation cyclic power supply task is conducted to generate a power supply switching timing evaluation set to be processed.

[0022] Preferably, the process involves collecting the electrical hardware information of the target power supply battery pack and identifying the high-voltage electrical circuits of the vehicle to obtain the electrical circuit identification results. This specifically includes the following steps:

[0023] Collect the physical interface information of the target battery pack's hardware, which includes positive and negative relays, main relays, dual power switch, DC-DC converter, MPPT charging controller, rectifier, charger, voltage and current sensor, and drive motor.

[0024] Collect network connection parameters of the vehicle's DC circuit and AC power generation circuit;

[0025] By combining hardware physical interface information and power generation circuit network connection parameters, the electrical circuit identification result is obtained by identifying the appropriate electrical circuit standard.

[0026] Preferably, based on the electrical circuit identification results and the characteristics of the linked cyclic power supply, electrical circuit adaptation processing is performed on the tasks at each level in the result set of the linked cyclic power supply task to generate a set of linked cyclic power supply tasks to be executed. Specifically, this includes the following steps:

[0027] Based on the electrical circuit identification results and the priority level of the coaxial generator linkage rules, the high-voltage electrical control parameters of the cyclic power supply task are adjusted to obtain the parameter adjustment results;

[0028] Extract the switching execution node positions of each level of the cyclic power supply linkage task result set, and combine the parameter adjustment results to complete the high voltage signal conversion and rectification charging data format standardization processing of each level of task to generate the cyclic power supply task dataset;

[0029] Verify the pre-power supply switching conditions and post-energy storage generation status output results of each task in the cyclic power supply task dataset, and generate a verification result set.

[0030] Extract the dataset of power generation and power supply execution dependencies between cyclic power supply linkage tasks, and combine it with the verification result set to preprocess and sort all hierarchical tasks to obtain the set of cyclic power supply linkage tasks to be executed.

[0031] Preferably, extracting key dual-power automatic switching trigger nodes from the result set of the cyclic power supply linkage task specifically includes the following steps:

[0032] Extract the operating condition trigger data corresponding to high-priority coaxial power generation linkage tasks from the verification result set;

[0033] By combining the operating condition trigger data and the location of the task switching execution nodes at each level, the key dual power supply automatic switching trigger nodes are determined based on the result set of the cyclic power supply linkage task.

[0034] Preferably, the coaxial power generation and charging / discharging linkage execution records of key dual-power automatic switching trigger nodes are obtained, and a set of reliability assessment results for the pending cyclic power supply is generated by combining the dual-power switching trigger condition dataset. This specifically includes the following steps:

[0035] Obtain the coaxial power generation charging and discharging linkage execution records of key dual power supply automatic switching trigger nodes to generate a set of coaxial power generation power supply behavior trajectories for dual battery packs;

[0036] The charging, discharging, and power generation actions of the two batteries, DC motor, and axial flux AC generator within the coaxial power generation behavior trajectory set of the dual-battery pack are analyzed to generate a third electrical interaction performance dataset.

[0037] By combining the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, the stability of the dual-battery pack coaxial integrated power generation cyclic power supply task is evaluated, and the reliability evaluation result set of the cyclic power supply to be executed is obtained.

[0038] Preferably, the process of obtaining the coaxial power generation and charging / discharging linkage execution records of key dual-power automatic switching trigger nodes to generate a set of coaxial power generation and supply behavior trajectories for dual battery packs specifically includes the following steps:

[0039] Acquire all historical power generation and charging / discharging records of key dual-power automatic switching trigger nodes, collect switching timestamps, DC motor start / stop sequences, and axial flux generator power output sequences, and construct a set of coaxial power generation and supply behavior trajectories for dual-battery packs.

[0040] Preferably, the charging, discharging, and power generation actions of the two battery packs, DC motor, and axial flux AC generator within the coaxial power generation behavior trajectory set of the dual-battery pack are analyzed to generate a third electrical interaction performance dataset, specifically including the following steps:

[0041] Extract the battery power supply and generator unit power generation action records corresponding to the first switching trigger condition set in the dual-battery pack coaxial power generation and supply behavior trajectory set, and generate the first power supply behavior trajectory subset;

[0042] Extract the battery power supply and generator unit power generation action records corresponding to the second switching trigger condition set in the dual-battery pack coaxial power generation behavior trajectory set, and generate a subset of the second power supply behavior trajectory.

[0043] Calculate the timing deviations of battery switching and unit start-up / shutdown actions within the first power supply behavior trajectory subset and the second power supply behavior trajectory subset, and output the deviation dataset;

[0044] Based on the deviation dataset, the synchronization and consistency of the dual-battery power supply and discharge and the coaxial unit power generation are determined, and a third electrical interaction performance dataset is generated.

[0045] Preferably, the stability of the dual-battery pack coaxial integrated power generation cycle power supply task is evaluated by combining the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, resulting in a reliability evaluation result set for the cycle power supply to be executed. This specifically includes the following steps:

[0046] Based on the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, the reliability of cyclic power supply operation under abnormal conditions such as power loss, insufficient motor torque, generator power fluctuation, and high-voltage line circuit breaker is evaluated to obtain the cyclic power supply reliability evaluation result set to be executed.

[0047] Compared with existing technologies, this invention has the following advantages: By collecting dual-battery pack status datasets and coaxial power generation charging and discharging linkage execution parameter sets, intelligent load allocation is achieved. The two battery packs alternately share the vehicle load, and the coaxial DC motor and AC generator work together to generate electricity in a cyclic manner, effectively extending the driving range with the same total battery weight. By completing the full-dimensional data collection of the whole vehicle, the analysis of linkage power supply characteristics, the hierarchical decomposition of tasks, the adaptation of high-voltage circuits, the timing evaluation, and the reliability verification, a standardized and complete control system is formed, realizing the full-domain collaborative management and control of battery power supply and coaxial generator power generation. By performing priority classification judgment on the linkage cyclic power supply characteristics, multi-level cyclic power supply linkage tasks are generated, and then the electrical circuit adaptation processing is completed in combination with the electrical circuit identification results to generate a set of tasks to be executed. The task execution order can be distinguished according to the weight of driving safety, battery protection, and vehicle energy efficiency, and the output load of the two battery packs can be dynamically allocated, avoiding the long-term continuous exposure of a single battery pack to high current impact, slowing down the battery degradation rate, and extending the service life of the power battery. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating a method for cyclic power supply of new energy vehicles based on alternating dual-battery-pack power supply, as provided in an embodiment of the present invention.

[0049] Figure 2 This is a flowchart illustrating the process of generating a set of cyclic power supply linkage tasks to be executed in a new energy vehicle cyclic power supply method based on alternating dual battery pack power supply, as provided in an embodiment of the present invention. Detailed Implementation

[0050] 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.

[0051] 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.

[0052] 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.

[0053] Reference Figures 1-2 As shown.

[0054] The embodiments further illustrate the new energy vehicle cyclic power supply method based on alternating dual-battery pack power supply proposed in this invention.

[0055] A method for cyclic power supply of new energy vehicles based on alternating power supply from dual battery packs, the method comprising the following specific steps:

[0056] Collects equipment status data information of the vehicle's electrical circuits and control commands for the integrated cycle power generation of the vehicle's three electric systems; the equipment status data information includes dual battery pack status datasets, dual power supply switching trigger condition datasets, and coaxial power generation charging and discharging linkage execution parameter sets.

[0057] The dual-battery pack status dataset and the dual-power switching trigger condition dataset specifically include the following steps:

[0058] Based on the timing switching conditions of the key dual-power automatic switching trigger node, the dual-battery pack cycle charge-discharge cycle and the coaxial unit start-stop time window are marked as the first switching trigger condition set; the dual-battery pack BMS time synchronization status and historical cycle power generation execution records are collected to generate the first dual-battery pack status dataset.

[0059] Based on the operating condition switching conditions of the key dual-power automatic switching trigger node, the dual-battery pack SOC switching threshold, DC motor torque and speed threshold, and axial flux AC generator output power threshold are marked as the second switching trigger condition set; among them, the DC motor output torque is more than 20% greater than the coaxial AC generator torque, and the axial flux generator power generation power is 4-8 times the DC motor power consumption power; real-time voltage and current of the dual-battery pack, DC motor operating parameters, generator output power, and vehicle drive motor and air conditioning load feedback signals are collected to generate the second dual-battery pack status dataset;

[0060] Based on the combined switching conditions of key dual-power automatic switching trigger nodes, the mutual power supply logic of dual battery A and battery B, and the coaxial linkage start-stop rules of DC motor and AC generator are marked as the third switching trigger condition set; the cross-loop interaction logs of dual power switch, MPPT charging controller, and main controller, and the complete alternating power generation execution records are collected to generate the third dual-battery group status dataset.

[0061] The first switching trigger condition set, the second switching trigger condition set, and the third switching trigger condition set are combined to form a dual power supply switching trigger condition dataset; the first dual battery pack status dataset, the second dual battery pack status dataset, and the third dual battery pack status dataset are merged to form a dual battery pack status dataset.

[0062] The first set of switching trigger conditions is defined based on the timing switching conditions of the key dual-power automatic switching trigger nodes. This set uses a fixed time period as the basis for switching, records the complete cycle charging and discharging time interval of the dual batteries, the time window for the coaxial unit to start and stop, synchronously collects the synchronization clock deviation of the dual battery pack BMS, and the storage records of past complete cycle power generation, and summarizes all timing and historical operating information to generate the first dual battery pack status dataset, which is used for power switching determination in timing mode.

[0063] A second set of switching trigger conditions is defined based on the operating condition switching criteria, and the dual-battery SOC switching threshold, DC motor torque and speed threshold, and axial flux alternator output power threshold are marked. Simultaneously, equipment power matching constraints are preset, calculated as follows: Equipment power matching constraint value = DC motor output torque value ÷ alternator torque value. The axial flux alternator power output value falls within the range of DC motor power consumption multiplied by 4 to DC motor power consumption multiplied by 8. The system synchronously collects real-time output voltage and current of the dual batteries, DC motor speed and torque operating parameters, alternator instantaneous output power, and power feedback signals from the vehicle drive motor and air conditioning load. All voltage units are converted to volts, current units to amperes, and power units to kilowatts. This real-time electrical load data is integrated to generate a second dual-battery pack status dataset for switching determination under dynamic driving conditions.

[0064] The third switching trigger condition set is defined based on the combined switching conditions. The logical sequence of power switching between battery A and battery B is recorded, as well as the coaxial linkage synchronous start-stop constraint rules of DC motor and AC generator. The action logs of dual power switch, MPPT charging controller adjustment records, vehicle main controller cross-high voltage circuit interaction logs, and historical execution records of alternating power generation throughout the entire process are collected simultaneously. The hardware interaction logs are integrated to generate the third dual battery pack status dataset, which is used for switching determination in multi-condition composite trigger scenarios.

[0065] After the system independently constructs the three types of condition sets and the three types of status datasets, it performs a merging operation. It integrates and removes duplicates from the first, second, and third switching trigger condition sets, unifies the data storage format to form a complete dual-power switching trigger condition dataset, and then merges and summarizes the first, second, and third dual-battery pack status datasets, removes duplicate collected device parameters, and forms a complete dual-battery pack status dataset. The two datasets fully cover the judgment parameters for the three types of switching scenarios under timed operating conditions.

[0066] Taking the urban constant speed cruise condition as an example, the timed switching condition set sets the battery charge and discharge cycle to 1200 seconds, the condition switching condition set sets the SOC switching threshold to 25%, the motor torque to 100 Nm, and the generator power to meet the motor power consumption multiplied by 6. The combined condition set sets the two battery groups to alternately supply power when the battery level is below the threshold. The system collects three types of state data of real-time electrical hardware interaction corresponding to the BMS time sequence, generates three subsets respectively, and merges them to obtain the complete dual power supply switching trigger condition dataset and dual battery group state dataset, which are used for subsequent electrical interaction performance calculation.

[0067] The linkage and cyclic power supply characteristics of the target power supply battery pack, the coaxial DC motor and AC generator of the dual battery pack are obtained in the integrated cyclic power generation control command of the vehicle's three electric systems.

[0068] Prioritize and classify the characteristics of the linked cyclic power supply to obtain the result set of the linked cyclic power supply task, and generate a set of linked cyclic power supply tasks to be executed based on the result set of the linked cyclic power supply task.

[0069] Based on the key dual-power automatic switching trigger nodes, vehicle electrical circuit equipment status data, and electrical interaction data between the dual battery packs and the coaxial generator set, a power switching timing evaluation set to be processed is generated from the results of the cyclic power supply linkage task.

[0070] Obtain the coaxial power generation charging and discharging linkage execution records of key dual power supply automatic switching trigger nodes, and generate a set of reliability assessment results for the cyclic power supply to be executed by combining the dual power supply switching trigger condition dataset;

[0071] By integrating the set of pending cyclic power supply linkage tasks, the set of pending power supply switching timing evaluations, and the set of pending cyclic power supply reliability evaluation results, a cyclic power supply execution scheme for alternating power supply from dual battery packs and coaxial motor generators is obtained.

[0072] The priority classification of the linked cyclic power supply characteristics is used to obtain the cyclic power supply linkage task result set. Based on the cyclic power supply linkage task result set, a set of cyclic power supply linkage tasks to be executed is generated, which specifically includes the following steps:

[0073] Priority classification is performed on the characteristics of the linked cyclic power supply to obtain the cyclic power supply linkage task. The cyclic power supply linkage task is then decomposed into a hierarchical structure to obtain the cyclic power supply linkage task result set.

[0074] Collect the electrical hardware information of the target power supply battery pack and identify the high-voltage electrical circuits of the vehicle to obtain the electrical circuit identification results;

[0075] Based on the electrical circuit identification results and the characteristics of the linked cyclic power supply, electrical circuit adaptation processing is performed on each level of the cyclic power supply linkage task result set to generate a set of cyclic power supply linkage tasks to be executed.

[0076] The system retrieves the parsed linked cyclic power supply characteristics and prioritizes them according to three weights: power supply safety, battery protection, and vehicle energy efficiency. The weight values ​​are set to 50, 30, and 20 respectively, and the total weight is calculated as: Total Weight = Safety Weight + Battery Weight + Energy Efficiency Weight, corresponding to a total weight of 50 + 30 + 20 = 100. The system uses this total weight to distinguish the execution order of different power supply tasks. After the priority judgment is completed, a single cyclic power supply linkage task is generated. The system then performs a hierarchical decomposition operation on this task, dividing it into three levels: top-level scheduling, middle-level switching, and bottom-level execution. The top-level scheduling level selects the target battery pack for the current power output; the middle-level switching level controls the on / off timing of the dual power supply switching switch; and the bottom-level execution level controls the output power of the coaxial DC motor and AC generator. After all levels are decomposed, they are integrated to form the cyclic power supply linkage task result set.

[0077] The system synchronously and in parallel carries out the hardware identification process, continuously collecting basic information such as rated voltage, rated current carrying time, and rated power loss of the high-voltage contactor insulation detection module and current acquisition module matched with the currently selected target power supply battery pack. The hardware parameters are imported into the vehicle's high-voltage electrical circuit topology model to complete the circuit scanning and identification. The identification process determines the circuit's compatibility range by calculating the total circuit load power. The calculation formula is: Total circuit load power = Single branch electrical power 1 + Single branch electrical power 2 + Single branch electrical power 3. All branch power units are uniformly converted to kilowatts before being superimposed. The calculated total circuit load power value is the core judgment indicator of the electrical circuit identification result, and the complete electrical circuit identification result is output.

[0078] Using the electrical circuit identification results and the original linked cyclic power supply characteristics as the calculation benchmark, electrical circuit adaptation processing is performed on each level of tasks within the cyclic power supply linkage task result set, at the top-level scheduling level, the middle-level switching level, and the bottom-level execution level. The adaptation process compares the preset output power of each task level with the total load power of the circuit. When the preset output power of the task is greater than the total load power of the circuit, the output parameters of the coaxial generator set are reduced. The calculation formula is: Reduction Amount = Preset Output Power of Task - Total Load Power of Circuit. When the preset output power of the task is less than the total load power of the circuit, a short-term parallel charging mode for the two battery sets is simultaneously activated. The calculation formula is: Charging Power Difference = Total Load Power of Circuit - Preset Output Power of Task. After completing the adaptation correction for power matching, timing matching, and hardware parameter matching for all levels of tasks, invalid tasks that conflict with the high-voltage circuit hardware parameters are eliminated, and the remaining corrected standardized tasks are integrated to form a set of cyclic power supply linkage tasks to be executed.

[0079] Taking the high-speed cruising condition of the vehicle as an example, the system first determines that the range safety has the highest weight, and then generates a basic linkage task for switching the auxiliary battery pack to supply power separately after classification. This task is broken down into the top-level task of selecting the auxiliary battery, the middle-level task of disconnecting the main battery circuit switch, and the bottom-level task of controlling the generator to provide a small amount of power. The task results are stored in the task result set. At the same time, the auxiliary battery, the matching contactor, and the rated current are collected. The total load power value of the vehicle's high-voltage circuit is identified as 45 kilowatts. The system performs adaptation calculations based on the preset output power of 40 kilowatts for the three-level tasks. The power difference is 45-40=5 kilowatts. The system adjusts the output power of the bottom-level generator to increase by 5 kilowatts. After completing the adaptation and correction of all levels, the system outputs a set of pending cyclic power supply linkage tasks that can be directly called by the vehicle's three-electric controller.

[0080] Based on the key dual-power automatic switching trigger nodes, vehicle electrical circuit equipment status data, and electrical interaction data between the dual battery packs and the coaxial generator set, a power switching timing evaluation set to be processed is generated, which includes the following steps:

[0081] Extract key dual-power automatic switching trigger nodes from the results of the cyclic power supply linkage task;

[0082] Based on the key dual-power automatic switching trigger node, the alternating power supply switching conditions of the dual battery packs are preset. According to the matching degree between the alternating power supply switching conditions of the dual battery packs and the dual battery pack status dataset, and the power transmission delay data from the dual battery packs to the coaxial generator set, the first electrical interaction performance dataset is generated.

[0083] A second electrical interaction performance dataset is generated based on the matching degree between the alternating power supply switching conditions of the dual battery packs and the dual battery pack state dataset, as well as the synchronization deviation data of the dual battery pack output voltage.

[0084] By combining the first electrical interaction performance dataset, the second electrical interaction performance dataset, the dual battery pack status dataset, and the coaxial power generation charging and discharging linkage execution parameter set, a comprehensive evaluation of the switching timing of the dual battery pack coaxial integrated power generation cyclic power supply task is conducted to generate a power supply switching timing evaluation set to be processed.

[0085] The system performs data extraction operations independently, directly reading all action nodes stored in the result set of the cyclic power supply linkage task, and filtering out the key dual-power automatic switching trigger node that marks the switching of the two sets of battery power supply states. This node records three basic timing reference information at the time of switching start: target battery switching direction, switching target, and power. It serves as the time reference standard for all subsequent electrical performance calculations.

[0086] Based on the extracted switching trigger nodes, standardized dual-battery pack alternating power supply switching conditions are set. The switching conditions include two types of judgment indicators: battery remaining power threshold and output power upper limit. The system first calculates the matching degree between the switching conditions and the real-time dual-battery pack status dataset. The calculation formula is: matching degree value = number of parameters that meet the conditions ÷ total number of judgment parameters × 100. The calculated value is uniformly converted to a percentage. At the same time, the power transmission delay data from the dual-battery pack to the coaxial generator set is retrieved. The delay data is uniformly converted to milliseconds. The matching degree value and the transmission delay value are bound one-to-one. All corresponding values ​​are integrated to form the first electrical interaction performance dataset. This dataset is used to measure the time lag of the power transmission link.

[0087] The system reuses the same set of dual-battery pack alternating power supply switching conditions and dual-battery pack status dataset matching degree values, retrieves the real-time output voltage synchronization deviation data of the two battery packs, converts the voltage deviation unit to volts, completes the data pairing and storage of matching degree values ​​and voltage deviation values, and generates a second electrical interaction performance dataset. This dataset is used to measure the voltage synchronization stability of the two battery packs at the moment of switching, and avoids voltage surge damage to the vehicle's high-voltage components at the moment of switching.

[0088] The comprehensive timing evaluation operation is initiated. The input includes four types of data: the first electrical interaction performance dataset, the second electrical interaction performance dataset, the dual battery pack status dataset, and the coaxial power generation charging and discharging linkage execution parameter set. The operation is carried out in two layers. The first layer reads the transmission delay value of the first electrical interaction performance dataset to calculate the timing compensation amount. The calculation formula is: timing compensation amount = power transmission delay value + voltage synchronization deviation value. The second layer combines the real-time remaining battery power and the generator set's allowable charge and discharge rate to correct the switching start time. All indicators, including the compensated switching start time, switching duration, and switching completion verification threshold, are summarized to complete a comprehensive evaluation of the switching timing of the dual battery pack coaxial integrated power generation cycle power supply task. All evaluation indicators are integrated to form the power supply switching timing evaluation set to be processed.

[0089] Taking the low-speed hill climbing condition of the vehicle as an example, the system first extracts the key trigger node of switching the power supply battery when the battery level is below 20% from the task result set. The switching conditions are set as the remaining power of a single battery group is less than 20%, the real-time battery data matching degree is equal to 95%, and the power transmission delay is equal to 12 milliseconds. The first electrical interaction performance dataset is generated. The same matching degree is combined with a voltage synchronization deviation of 3 volts to generate the second electrical interaction performance dataset. The remaining power of the two battery groups and the generator charge and discharge rate parameters are retrieved to carry out a comprehensive evaluation. The calculation formula is: timing compensation amount = 12 + 3 = 15 milliseconds. The system completes the timing correction of the overall switching action 15 milliseconds in advance. The corrected switching start time verification index is summarized to form the power supply switching timing evaluation set corresponding to this working condition.

[0090] Collect the electrical hardware information of the target power supply battery pack, identify the high-voltage electrical circuits of the vehicle to obtain the electrical circuit identification results, specifically including the following steps:

[0091] Collect the physical interface information of the target battery pack's hardware, which includes positive and negative relays, main relays, dual power switch, DC-DC converter, MPPT charging controller, rectifier, charger, voltage and current sensor, and drive motor.

[0092] Collect network connection parameters of the vehicle's DC circuit and AC power generation circuit;

[0093] By combining hardware physical interface information and power generation circuit network connection parameters, the electrical circuit identification result is obtained by identifying the appropriate electrical circuit standard.

[0094] The system performs data collection on the physical interfaces of the target battery pack's hardware, covering all associated high-voltage components. These components include positive and negative relays, main relays, dual-power switchers, DC-DC converters, MPPT charging controllers, rectifiers, chargers, voltage and current sensors, and drive motors. The collected data includes parameters such as the rated current carrying capacity of each hardware interface, the interface withstand voltage, and the interface conduction response time. All current values ​​are uniformly converted to amperes, voltage values ​​to volts, and time values ​​to milliseconds. The maximum load capacity of a single hardware interface is calculated as follows: Maximum load capacity of a single hardware interface = Rated current carrying capacity of the interface × Interface withstand voltage. This value represents the maximum power that the hardware interface can stably carry and is the basic hardware constraint for loop identification.

[0095] Synchronously collect the network connection parameters of two types of electrical circuits in the whole vehicle. The two types of circuits are the DC circuit and the AC power generation circuit respectively. The collected content includes the number of branches, the series resistance of the branches, the number of parallel loads of the branches, and the loop transmission loss coefficient. The resistance value is uniformly converted to ohms, and the loss coefficient is a dimensionless percentage value. The calculation method of the total transmission loss of the whole vehicle loop is: the total transmission loss of the whole vehicle loop = single-branch loss coefficient 1 + single-branch loss coefficient 2 + single-branch loss coefficient 3. This calculated value is used to measure the power loss degree of electric energy during the loop transmission process and can reflect the electrical adaptation ability of the loop networking structure.

[0096] Carry out loop standard matching recognition operations. When performing the operations, retrieve all hardware physical interface information and AC / DC loop network connection parameters, and perform hardware load matching verification on each loop branch one by one. The calculation formula is: the maximum allowable power of the branch = the minimum value of the load upper limit of all hardware interfaces of the branch, and the actual operating power of the branch = the sum of the parallel load powers of the branch. After comparing these two values, determine whether the current branch meets the requirements of the standard electrical loop. If the actual operating power of the branch is less than or equal to the maximum allowable power of the branch, it is determined that the branch meets the electrical loop standard for adaptation; otherwise, it is determined that there is a hardware overload risk for the branch. After completing the verification of all branches one by one, summarize the determination conclusions of all branches, and integrate them to form a complete electrical loop recognition result. The recognition result records three core information: the hardware matching status, power difference, and transmission loss value of each branch.

[0097] Taking the vehicle's high-speed constant-speed driving condition as an example, the system selects the main battery pack as the target power supply battery pack, collects the interface parameters of 9 types of high-voltage hardware supporting the main battery, calculates that the load upper limit value of the drive motor hardware interface is equal to 75,000 watts, synchronously collects the network parameters of the vehicle's DC drive loop and the AC coaxial generator power generation loop, the total transmission loss value of the whole vehicle loop is equal to 8%, the sum of the parallel load powers of the drive loop branches is equal to 52,000 watts, the maximum allowable power of the branch is taken as 75,000 watts, and the actual operating power of the branch of 52,000 watts is less than the maximum allowable power of the branch. It is determined that the branch meets the electrical loop standard for adaptation. After completing the verification of all branches, summarize the matching data of each branch, generate the electrical loop recognition result under the corresponding condition, and supply it for subsequent power supply task adaptation links to call.

[0098] Based on the electrical loop recognition result and the characteristics of the linked cyclic power supply, perform electrical loop adaptation processing on each level of tasks in the linked cyclic power supply task result set to generate a set of pending cyclic power supply linkage tasks to be executed, which specifically includes the following steps:

[0099] Adjust the high-voltage electrical control parameters of the cyclic power supply task according to the priority level of the electrical loop recognition result and the coaxial power generation linkage rules to obtain the parameter adjustment result;

[0100] Extract the switching execution node positions of each level of the cyclic power supply linkage task result set, and combine the parameter adjustment results to complete the high voltage signal conversion and rectification charging data format standardization processing of each level of task to generate the cyclic power supply task dataset;

[0101] Verify the pre-power supply switching conditions and post-energy storage generation status output results of each task in the cyclic power supply task dataset, and generate a verification result set.

[0102] Extract the dataset of power generation and power supply execution dependencies between cyclic power supply linkage tasks, and combine it with the verification result set to preprocess and sort all hierarchical tasks to obtain the set of cyclic power supply linkage tasks to be executed.

[0103] The system reads the hardware load limit and circuit loss values ​​of each branch in the electrical circuit identification results. At the same time, it retrieves the priority levels 1 to 5 of the coaxial generator linkage rules. The smaller the level number, the higher the execution priority. The high-voltage electrical control parameters corresponding to the cyclic power supply task are adjusted according to the priority weight. The calculation formula is: Branch allowable power difference = Branch hardware load limit - Task original output power. If the power difference is less than 0, the task output current is reduced. The calculation formula is: Adjusted output current = Original output current × Branch hardware load limit ÷ Task original output power. The current unit is uniformly converted to amperes. After all parameters are corrected, the results are summarized to form the parameter adjustment results.

[0104] Extract the switching execution node positions corresponding to all levels of tasks in the top, middle, and bottom layers of the cyclic power supply linkage task result set. The node records the timing information of switching start time, duration, and switching action type. Combined with the parameter adjustment results, two types of standardization processing are carried out. The first type is high-voltage signal conversion, which uniformly scales the signal amplitude according to the circuit rated voltage. The second type is rectification and charging data format standardization, which unifies the data recording units of voltage, current, and duration. After all levels of tasks are processed, they are integrated to generate a cyclic power supply task dataset. The dataset stores the standardized power timing control signal, rectification, and charging data in multiple unified format formats.

[0105] For each independent task within the cyclic power supply task dataset, bidirectional logical verification is performed. The verification is divided into pre-power supply switching condition verification and post-energy storage and power generation status output verification. The pre-verification checks whether the battery power load power meets the switching start threshold before the task starts. The post-verification calculates the amount of electricity that the coaxial generator can replenish after the task ends. The amount of electricity that can be recharged at one time = power generation power × task execution time. The power unit is converted to kilowatt-hours and the length unit is converted to hours. The electricity unit is uniformly kilowatt-hours. When both verifications are met, the task is marked as valid. If either one fails, the task is marked as needing secondary correction. After all task verifications are completed, the marking information is summarized to generate a verification result set.

[0106] Extract the dataset of power generation and power supply execution dependencies that are bound together by all cyclic power supply linkage tasks. This dataset records the sequential triggering constraints, parallel constraints, and timing interval constraints between tasks. Merge the dependency dataset with the verification result set, filter out tasks marked as invalid, and sort the remaining valid tasks according to the dual criteria of execution dependency order and original priority level. The calculation formula is: sorting weight value = priority corresponding score + previous task completion progress score. The larger the value, the higher the execution priority of the task. After all levels of tasks are preprocessed and sorted, they are integrated to obtain the final set of cyclic power supply linkage tasks to be executed.

[0107] Taking the low-speed operation under urban congestion as an example, the electrical circuit identification result shows that the upper limit of the hardware load of the drive branch is equal to 60 kilowatts, the output power of the original mid-level switching task is equal to 68 kilowatts, and the power difference is 60-68=-8. After the system converts and adjusts, the output current completes the parameter adjustment. The three-level task switching nodes are extracted to standardize the high-voltage signal and rectified data to generate a task dataset. The rechargeable power of each task is calculated to complete the bidirectional verification and obtain the verification result set. The effective tasks are sorted according to the task start dependency relationship, and finally the set of pending cyclic power supply linkage tasks adapted to the current high-voltage circuit operation is output.

[0108] Extracting key dual-power automatic switching trigger nodes from the results set of the cyclic power supply linkage task includes the following steps:

[0109] Extract the operating condition trigger data corresponding to high-priority coaxial power generation linkage tasks from the verification result set;

[0110] By combining the operating condition trigger data and the location of the task switching execution nodes at each level, the key dual power supply automatic switching trigger nodes are determined based on the result set of the cyclic power supply linkage task.

[0111] Data filtering and extraction operations are performed on the verification result set. The verification result set stores all hierarchical power supply tasks that have undergone pre- and post-verification. Each task is marked with an independent priority score, with the score range set from 1 to 10. The higher the value, the higher the task scheduling priority. The system sets the filtering threshold to 7 and only reads coaxial power generation linkage tasks with a priority score greater than or equal to 7. Simultaneously, the operating condition trigger data bound to this type of task is captured. The operating condition trigger data includes three quantitative parameters: vehicle driving load power, battery remaining power, and motor torque. All power values ​​are uniformly converted to percentages, power values ​​are uniformly converted to kilowatts, and torque values ​​are uniformly converted to Newton-meters. The calculation formula is: Operating condition matching judgment formula is Operating condition matching index = Real-time load power corresponding score + Battery remaining power corresponding score + Motor torque corresponding score. The index value is used to measure whether the current vehicle operating status meets the basic conditions for starting the coaxial power generation linkage task.

[0112] The system performs key node location calculations, simultaneously importing the operating condition trigger data and the switching execution node positions corresponding to all levels of tasks (top, middle, and bottom) within the cyclic power supply linkage task result set. The switching execution node positions record the time coordinates and power change amplitude corresponding to each on / off action, with the time unit uniformly converted to milliseconds. The system matches the operating condition matching index with the power change amplitude of each level of switching node. When the operating condition matching index reaches a preset trigger threshold, and the power change amplitude of the switching node exceeds the standard value of the steady-state output power difference of a single battery pack, the switching node is determined to have power switching trigger attributes. The system completes the location marking, and all nodes that meet the dual judgment conditions are integrated and summarized to form complete information on key dual-power automatic switching trigger nodes.

[0113] Taking the long-distance uphill driving condition of the vehicle as an example, the priority score of the coaxial generator linkage task in the verification result set is equal to 9, which is greater than the screening threshold of 7. The system extracts the trigger data of this task condition. The real-time load power corresponds to a score of 35, the remaining battery power corresponds to a score of 32, and the motor torque corresponds to a score of 33. The condition matching index = 35 + 32 + 33 = 100, which meets the start threshold standard. The system retrieves the switching execution node position of the three-layer task in the cyclic power supply linkage task result set. The power change amplitude of the middle layer switching node is equal to 12 kilowatts, which exceeds the steady-state power difference standard value of 5 kilowatts. The system marks this middle layer node as a key dual power automatic switching trigger node and extracts all the information of the start time power switching amplitude corresponding to this node for use in the subsequent power supply switching timing evaluation stage.

[0114] Obtain the coaxial power generation and charging / discharging linkage execution records of key dual-power automatic switching trigger nodes, and generate a set of reliability assessment results for the pending cyclic power supply by combining the dual-power switching trigger condition dataset. The specific steps include:

[0115] Obtain the coaxial power generation charging and discharging linkage execution records of key dual power supply automatic switching trigger nodes to generate a set of coaxial power generation power supply behavior trajectories for dual battery packs;

[0116] The charging, discharging, and power generation actions of the two batteries, DC motor, and axial flux AC generator within the coaxial power generation behavior trajectory set of the dual-battery pack are analyzed to generate a third electrical interaction performance dataset.

[0117] By combining the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, the stability of the dual-battery pack coaxial integrated power generation cyclic power supply task is evaluated, and the reliability evaluation result set of the cyclic power supply to be executed is obtained.

[0118] The system retrieves all coaxial power generation charging and discharging linkage execution records corresponding to the key dual-power automatic switching trigger nodes. The records store the historical switching time, charging and discharging current of the two battery groups, operating speed of the coaxial DC motor, and output power of the axial flux AC generator. The current unit is uniformly converted to amperes, the speed unit is uniformly converted to revolutions per minute, and the power unit is uniformly converted to kilowatts. The system stores all time-series operation data under the same trigger node in an orderly manner according to the time sequence, and integrates them to form a set of dual-battery coaxial power generation and supply behavior trajectories. The trajectory set completely restores the continuous operation process of the entire set of electrical equipment during each power switching process.

[0119] The action sequence of the four core devices within the behavior trajectory set is analyzed item by item. The four devices are the first battery pack, the second battery pack, the DC motor, and the axial flux AC generator. The analysis process calculates the battery charge-discharge fluctuation difference, the motor speed fluctuation value, and the generator output power response delay time for each single switch. The calculation formulas are: battery charge-discharge fluctuation difference = peak output current at the moment of switching - steady-state operating current; speed fluctuation value = highest speed at the moment of switching - reference stable speed; and the power response delay time is uniformly converted to milliseconds. All the fluctuation and delay values ​​obtained from the analysis are mapped one by one to the device operation sequence. All quantitative indicators are summarized to generate the third electrical interaction performance dataset. This dataset intuitively reflects the electrical fluctuation level of the entire power supply system under the switching node.

[0120] The system initiates a comprehensive reliability assessment calculation, simultaneously importing the third electrical interaction performance dataset and the dual-power switching trigger condition dataset. Three judgment criteria are used: the switching trigger condition dataset, the stored battery power threshold, and the allowable range of load power upper limit voltage fluctuation. The system sets a power supply stability score calculation formula: Power supply stability score = 100 - battery charging / discharging fluctuation difference × 1.2 - motor speed fluctuation value × 0.8 - generator power response delay time × 0.5. The score range is 0 to 100; a higher score indicates stronger stability in this cyclic power supply task. The system substitutes the fluctuation values ​​corresponding to each task into the formula to complete the score calculation, checks whether the current fluctuation values ​​are within the allowable range against the switching trigger condition dataset, simultaneously marks the task risk level, summarizes the stability scores and risk marking information of all tasks, and generates a set of reliability assessment results for the pending cyclic power supply task.

[0121] Taking the high-speed overtaking scenario as an example, the system retrieves historical linkage execution records of the switching node triggered by the battery level dropping to 25% to generate a behavior trajectory set. The analysis reveals that the battery charging and discharging fluctuation difference is equal to 6 amps, the motor speed fluctuation is equal to 120 revolutions per minute, and the generator power response delay time per minute is equal to 18 milliseconds. Substituting these values ​​into the formula, the power supply stability score is 100 - 6 × 1.2 - 120 × 0.8 - 18 × 0.5 = 23.8. Comparing the switching trigger condition dataset, it is found that the current and speed fluctuations exceed the allowable standards, marking the task as having a switching impact risk. The score value and the risk mark are stored together in the power supply reliability assessment result set of the corresponding cycle to be executed for this scenario, for use in the subsequent multi-dataset fusion to generate the power supply execution plan.

[0122] The process of obtaining the coaxial power generation charging and discharging linkage execution records of key dual-power automatic switching trigger nodes to generate a set of coaxial power generation power supply behavior trajectories for dual battery packs includes the following steps:

[0123] Acquire all historical power generation and charging / discharging records of key dual-power automatic switching trigger nodes, collect switching timestamps, DC motor start / stop sequences, and axial flux generator power output sequences, and construct a set of coaxial power generation and supply behavior trajectories for dual-battery packs.

[0124] The system retrieves all historical power generation and charging / discharging records stored at a designated key dual-power automatic switching trigger node. These records are stored in the local storage unit of the vehicle's three-electric controller, completely preserving all operational data generated during each power switching process at that node, with no missing time segments. The system simultaneously extracts three independent types of time-series data from the historical records: the first type is the switching timestamp, which marks the system timing values ​​corresponding to the start and end of each power switching action, uniformly converted to milliseconds, allowing for precise location of the switching action within the vehicle's operating cycle; the second type is the DC motor start / stop sequence, which systematically records the speed changes between the DC motor's start and stop times, uniformly converted to revolutions per minute (rpm); the third type is the axial flux generator power output sequence, which systematically stores the generator's steady-state output power before switching, instantaneous power fluctuations during switching, and stable power after switching, uniformly converted to kilowatts (kW).

[0125] The system binds and pairs the three types of time-series data one by one, using the same switching timestamp as a unified time-series benchmark. It associates and binds the DC motor start / stop data and axial flux generator power output data for the corresponding time period. The data capacity of a single complete trajectory unit is calculated as follows: Single unit data capacity = Timestamp storage bits + Motor sequence storage bits + Generator power sequence storage bits. All bound time-series units are arranged in ascending order according to the chronological order of the switching occurrence. A unified and standardized data storage format is used, and duplicate and redundant invalid historical records are removed. After integrating all valid time-series units, a complete set of dual-battery coaxial power generation and supply behavior trajectories is constructed. Each storage unit within this trajectory set can completely reconstruct the synchronous operation state of the DC motor and axial flux generator during a single dual-battery switching process, intuitively reflecting the dynamic electrical changes of the entire coaxial power generation system at the switching node.

[0126] Taking the vehicle climbing and battery depletion switching operation as an example, the system retrieves all historical charging and discharging records of the key switching trigger nodes corresponding to the remaining battery power being less than 20%, and collects 50 sets of switching timestamps. Each set of timestamps is matched with the corresponding DC motor start-stop speed sequence and axial flux generator power output sequence. The data capacity of a single unit is calculated to be equal to 128 bits. The system binds and arranges all 50 sets of time sequence units in chronological order, removes 3 sets of duplicate records, and finally generates a set of dual-battery pack coaxial power generation and supply behavior trajectories containing 47 sets of complete switching operation records, which are then used in the subsequent electrical interaction performance analysis stage.

[0127] The charging, discharging, and power generation actions of the two battery packs, DC motor, and axial flux AC generator within the coaxial power generation behavior trajectory set of the dual-battery pack are analyzed to generate a third electrical interaction performance dataset. The specific steps include:

[0128] Extract the battery power supply and generator unit power generation action records corresponding to the first switching trigger condition set in the dual-battery pack coaxial power generation and supply behavior trajectory set, and generate the first power supply behavior trajectory subset;

[0129] Extract the battery power supply and generator unit power generation action records corresponding to the second switching trigger condition set in the dual-battery pack coaxial power generation behavior trajectory set, and generate a subset of the second power supply behavior trajectory.

[0130] Calculate the timing deviations of battery switching and unit start-up / shutdown actions within the first power supply behavior trajectory subset and the second power supply behavior trajectory subset, and output the deviation dataset;

[0131] Based on the deviation dataset, the synchronization and consistency of the dual-battery power supply and discharge and the coaxial unit power generation are determined, and a third electrical interaction performance dataset is generated.

[0132] Read the complete set of behavior trajectories, filter all records that match the first switching trigger condition set. The first switching trigger condition set corresponds to the single battery low power switching condition. Extract the two sets of battery charging and discharging current timing, DC motor start and stop timing, and axial flux AC generator power output timing from the corresponding records. Convert all timing values ​​to milliseconds. Integrate all matching records to generate the first power supply behavior trajectory subset. The subset only stores the entire set of equipment linkage operation data under the low power switching scenario.

[0133] Based on the original behavior trajectory set, all records matching the second switching trigger condition set are filtered. The second switching trigger condition set corresponds to the high-load power switching condition of the whole vehicle. Similarly, the full-time action records of the battery power generation unit are extracted and organized into a second power supply behavior trajectory subset. The subset only stores the equipment linkage operation data under the high-power load scenario. After the two types of subsets are divided, the data isolation of the two typical switching conditions is achieved, which makes it easy to calculate the timing deviation separately.

[0134] Timing deviation calculations were performed by reading the battery switching start time and the coaxial generator start / stop start time for the same switching action within the two subsets. The calculation formula was: Single action timing deviation = Generator start / stop start time - Battery switching start time. The calculated values ​​were uniformly expressed in milliseconds. Positive values ​​indicated that the generator action lagged behind the battery switching, while negative values ​​indicated that the generator action preceded the battery switching. The timing deviation values ​​corresponding to all switching actions in the two subsets were systematically summarized to form a complete deviation dataset. The dataset intuitively recorded the time difference between the actions of the battery and the generator under different operating conditions.

[0135] Based on the deviation dataset, the synchronization performance is determined. The synchronization qualification threshold is set to 20 milliseconds. The synchronization score of a single action is 100 - the absolute value of the timing deviation value × 1.5, with a score range of 0 to 100. The higher the score, the better the synchronization consistency of the equipment actions. Each timing deviation value is matched one by one to complete the score calculation. The action records that meet the synchronization standard and exceed the synchronization tolerance are marked. All timing deviation values, synchronization scores, and working condition classification information are summarized to generate the third electrical interaction performance dataset.

[0136] Taking the high-load switching condition in urban congestion as an example, the battery switching start time of a certain record in the second power supply behavior trajectory subset is equal to 1200 milliseconds, the coaxial unit start-stop start time is equal to 1215 milliseconds, the single action timing deviation is 1215-1200=15 milliseconds, which does not exceed the 20 milliseconds qualified threshold, and the single action synchronization score is 100-15×1.5=77.5. The system marks the timing deviation synchronization score condition and stores it in the deviation dataset. After integrating all the calculation results of the two subsets, the third electrical interaction performance dataset is generated for use in the subsequent power supply stability assessment process.

[0137] The stability of the dual-battery pack coaxial integrated power generation cyclic power supply task is evaluated by combining the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, resulting in a reliability evaluation result set for the cyclic power supply task to be executed. The specific steps include:

[0138] Based on the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, the reliability of cyclic power supply operation under abnormal conditions such as power loss, insufficient motor torque, generator power fluctuation, and high-voltage line circuit breaker is evaluated to obtain the cyclic power supply reliability evaluation result set to be executed.

[0139] The system simultaneously retrieves the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset to perform cross-matching calculations. The third electrical interaction performance dataset stores the timing deviation and synchronization score of the battery and coaxial unit operation. The dual power supply switching trigger condition dataset presets four types of constraint parameters: critical power depletion capacity, minimum threshold for motor torque, allowable range for generator power fluctuation, and high-voltage line on / off judgment criteria. All power values ​​are uniformly converted to percentages, torque units are uniformly converted to Newton-meters, and power units are uniformly converted to kilowatts.

[0140] Independent reliability calculations were conducted for four typical abnormal operating conditions. The first condition was a low-power battery situation. The difference between the remaining battery power in the interactive dataset and the critical low-power level in the trigger condition set was calculated. The formula was: Low-power risk coefficient = Critical power level - Real-time remaining battery power level. A higher value indicates a higher risk of power failure due to low power. The second condition was insufficient motor torque. The formula was: Torque difference = Standard minimum torque value - Real-time motor output torque value. A torque difference greater than zero indicated a torque deficiency. The third condition was generator power fluctuation. The formula was: Power fluctuation amplitude = Instantaneous maximum output power - Instantaneous minimum output power. The amplitude was compared with the allowable fluctuation range to determine the fluctuation risk. The fourth condition was a high-voltage line open circuit situation. The circuit continuity was determined based on the timing synchronization score. A synchronization score below 30 indicated a potential high-voltage line open circuit fault.

[0141] The system uses a unified formula for calculating power supply reliability scores: Power Supply Reliability Score = 100 - Power Loss Risk Coefficient × 1.6 - Torque Difference × 0.9 - Power Fluctuation Amplitude × 0.7 - Deduction for Circuit Breaker Risk. The score ranges from 0 to 100, with higher scores indicating stronger stability in the current cyclic power supply task. The system substitutes all calculated values ​​from four operating conditions into the formula to calculate the score, simultaneously marking the abnormal operating condition type and risk level for each task. It then aggregates all reliability scores, risk markers, and operating condition calculation parameters to form a complete set of reliability assessment results for the pending cyclic power supply task.

[0142] Taking the long-distance uphill power depletion condition as an example, the dual power supply switching trigger condition set is as follows: the critical power depletion level is 20%, the real-time remaining battery power is 12%, the power depletion risk coefficient is 20-12=8, the real-time output torque of the motor is lower than the minimum standard, resulting in a torque difference of 12 Nm, the generator power fluctuation is 7 kW, the synchronization score is 22, triggering a circuit breaker risk and deducting 20 points, and the power supply reliability score is 100-8×1.6-12×0.9-7×0.7-20=49.1. The system records this score along with the risk markers of the four types of abnormal working conditions into the pending cyclic power supply reliability assessment result set, which is used in the subsequent multi-dataset fusion to generate the power supply execution plan.

[0143] 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.

[0144] 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 new energy vehicle circulating power supply method based on double battery pack alternating power supply, characterized in that, The method includes the following specific steps: Collects equipment status data information of the vehicle's electrical circuits and control commands for the integrated cycle power generation of the vehicle's three electric systems; the equipment status data information includes dual battery pack status datasets, dual power supply switching trigger condition datasets, and coaxial power generation charging and discharging linkage execution parameter sets; The linkage and cyclic power supply characteristics of the target power supply battery pack, the coaxial DC motor and AC generator of the dual battery pack are obtained in the integrated cyclic power generation control command of the vehicle's three electric systems. Prioritize and classify the characteristics of the linked cyclic power supply to obtain the result set of the linked cyclic power supply task, and generate a set of linked cyclic power supply tasks to be executed based on the result set of the linked cyclic power supply task. Based on the key dual-power automatic switching trigger nodes, vehicle electrical circuit equipment status data, and electrical interaction data between the dual battery packs and the coaxial generator set, a power switching timing evaluation set to be processed is generated from the results of the cyclic power supply linkage task. Obtain the coaxial power generation charging and discharging linkage execution records of key dual power supply automatic switching trigger nodes, and generate a set of reliability assessment results for the cyclic power supply to be executed by combining the dual power supply switching trigger condition dataset; By integrating the set of pending cyclic power supply linkage tasks, the set of pending power supply switching timing evaluations, and the set of pending cyclic power supply reliability evaluation results, a cyclic power supply execution scheme for alternating power supply from dual battery packs and coaxial motor generators is obtained.

2. The method according to claim 1, wherein, The priority classification of the linked cyclic power supply characteristics is used to obtain the cyclic power supply linkage task result set. Based on the cyclic power supply linkage task result set, a set of cyclic power supply linkage tasks to be executed is generated, which specifically includes the following steps: Priority classification is performed on the characteristics of the linked cyclic power supply to obtain the cyclic power supply linkage task. The cyclic power supply linkage task is then decomposed into a hierarchical structure to obtain the cyclic power supply linkage task result set. Collect the electrical hardware information of the target power supply battery pack and identify the high-voltage electrical circuits of the vehicle to obtain the electrical circuit identification results; Based on the electrical circuit identification results and the characteristics of the linked cyclic power supply, electrical circuit adaptation processing is performed on each level of the cyclic power supply linkage task result set to generate a set of cyclic power supply linkage tasks to be executed.

3. The method for cyclic power supply of new energy vehicles based on alternating dual-battery pack power supply according to claim 2, characterized in that, Based on the key dual-power automatic switching trigger nodes, vehicle electrical circuit equipment status data, and electrical interaction data between the dual battery packs and the coaxial generator set, a power switching timing evaluation set to be processed is generated, which includes the following steps: Extract key dual-power automatic switching trigger nodes from the results of the cyclic power supply linkage task; Based on the key dual-power automatic switching trigger node, the dual battery pack alternating power supply switching conditions are preset. According to the matching degree between the dual battery pack alternating power supply switching conditions and the dual battery pack status dataset, and the power transmission delay data from the dual battery pack to the coaxial generator set, the first electrical interaction performance dataset is generated. A second electrical interaction performance dataset is generated based on the matching degree between the alternating power supply switching conditions of the dual battery packs and the dual battery pack state dataset, as well as the synchronization deviation data of the dual battery pack output voltage. By combining the first electrical interaction performance dataset, the second electrical interaction performance dataset, the dual battery pack status dataset, and the coaxial power generation charging and discharging linkage execution parameter set, a comprehensive evaluation of the switching timing of the dual battery pack coaxial integrated power generation cyclic power supply task is conducted to generate a power supply switching timing evaluation set to be processed.

4. The method according to claim 3, wherein, Collect the electrical hardware information of the target power supply battery pack, identify the high-voltage electrical circuits of the vehicle to obtain the electrical circuit identification results, specifically including the following steps: Collect the physical interface information of the target battery pack's hardware, which includes positive and negative relays, main relays, dual power switch, DC-DC converter, MPPT charging controller, rectifier, charger, voltage and current sensor, and drive motor. Collect network connection parameters of the vehicle's DC circuit and AC power generation circuit; By combining hardware physical interface information and power generation circuit network connection parameters, the electrical circuit identification result is obtained by identifying the appropriate electrical circuit standard.

5. The method according to claim 4, wherein, Based on the electrical circuit identification results and the characteristics of linked cyclic power supply, electrical circuit adaptation processing is performed on each level of tasks in the cyclic power supply linkage task result set to generate a set of cyclic power supply linkage tasks to be executed. The specific steps include: Based on the electrical circuit identification results and the priority level of the coaxial generator linkage rules, the high-voltage electrical control parameters of the cyclic power supply task are adjusted to obtain the parameter adjustment results; Extract the switching execution node positions of each level of the cyclic power supply linkage task result set, and combine the parameter adjustment results to complete the high voltage signal conversion and rectification charging data format standardization processing of each level of task to generate the cyclic power supply task dataset; Verify the pre-power supply switching conditions and post-energy storage generation status output results of each task in the cyclic power supply task dataset, and generate a verification result set. Extract the dataset of power generation and power supply execution dependencies between cyclic power supply linkage tasks, and combine it with the verification result set to preprocess and sort all hierarchical tasks to obtain the set of cyclic power supply linkage tasks to be executed.

6. The method according to claim 5, wherein the method is characterized in that, Extracting key dual-power automatic switching trigger nodes from the results set of the cyclic power supply linkage task includes the following steps: Extract the operating condition trigger data corresponding to high-priority coaxial power generation linkage tasks from the verification result set; By combining the operating condition trigger data and the location of the task switching execution nodes at each level, the key dual power supply automatic switching trigger nodes are determined based on the result set of the cyclic power supply linkage task.

7. A method for cyclic power supply of new energy vehicles based on alternating dual-battery pack power supply according to claim 6, characterized in that, Obtain the coaxial power generation and charging / discharging linkage execution records of key dual-power automatic switching trigger nodes, and generate a set of reliability assessment results for the pending cyclic power supply by combining the dual-power switching trigger condition dataset. The specific steps include: Obtain the coaxial power generation charging and discharging linkage execution records of key dual power supply automatic switching trigger nodes to generate a set of coaxial power generation power supply behavior trajectories for dual battery packs; The charging, discharging, and power generation actions of the two batteries, DC motor, and axial flux AC generator within the coaxial power generation behavior trajectory set of the dual-battery pack are analyzed to generate a third electrical interaction performance dataset. By combining the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, the stability of the dual-battery pack coaxial integrated power generation cyclic power supply task is evaluated, and the reliability evaluation result set of the cyclic power supply to be executed is obtained.

8. The method according to claim 7, wherein, The process of obtaining the coaxial power generation and charging / discharging linkage execution records of key dual-power automatic switching trigger nodes to generate a set of coaxial power generation behavior trajectories for dual battery packs includes the following steps: Obtain all historical power generation and charging / discharging records of key dual-power automatic switching trigger nodes, collect switching timestamps, DC motor start / stop sequences, and axial flux generator power output sequences, and construct a set of coaxial power generation and supply behavior trajectories for dual-battery packs.

9. The method according to claim 8, wherein the method is characterized in that, The charging, discharging, and power generation actions of the two battery packs, DC motor, and axial flux AC generator within the coaxial power generation behavior trajectory set of the dual-battery pack are analyzed to generate a third electrical interaction performance dataset. The specific steps include: Extract the battery power supply and generator unit power generation action records corresponding to the first switching trigger condition set in the dual-battery pack coaxial power generation and supply behavior trajectory set, and generate the first power supply behavior trajectory subset; Extract the battery power supply and generator unit power generation action records corresponding to the second switching trigger condition set in the dual-battery pack coaxial power generation and supply behavior trajectory set, and generate the second power supply behavior trajectory subset; Calculate the timing deviations of battery switching and unit start-up / shutdown actions within the first power supply behavior trajectory subset and the second power supply behavior trajectory subset, and output the deviation dataset; Based on the deviation dataset, the synchronization and consistency of the dual-battery power supply and discharge and the coaxial unit power generation are determined, and a third electrical interaction performance dataset is generated.

10. The method according to claim 9, wherein the method is characterized in that, The stability of the dual-battery pack coaxial integrated power generation cyclic power supply task is evaluated by combining the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, resulting in a reliability evaluation result set for the cyclic power supply task to be executed. The specific steps include: Based on the third electrical interaction performance dataset and the dual power supply switching trigger condition dataset, the reliability of cyclic power supply operation under abnormal conditions such as power loss, insufficient motor torque, generator power fluctuation, and high-voltage line disconnection is evaluated to obtain the cyclic power supply reliability evaluation result set to be executed.

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