A fuel car oil changes electric platform car level battery pack management system

Abstract

The application provides a fuel car oil-to-electricity platform vehicle-grade battery pack management system, which is applied to the technical field of power battery management and comprises a distributed battery cell acquisition module, a vehicle interactive communication module, a multi-vehicle parameter database storage module, a main control module, a thermal management linkage control module and a positive balance driving module connected in sequence. The main control module calculates a comprehensive battery load characteristic value based on battery cell operation state data, vehicle driving state signals and matched vehicle platform parameters, and compares the comprehensive battery load characteristic value with a dynamic load threshold value; when the comprehensive battery load characteristic value is greater than the threshold value, output power limitation and graded thermal management adjustment are executed, otherwise, single positive balance processing based on battery cell pressure difference is executed; meanwhile, time sequence change characteristics of the processed operation state data are monitored, the dynamic load threshold value is adaptively adjusted and feedback adjustment is performed. The application realizes multi-vehicle adaptation and dynamic closed-loop control of battery load. In this way, the adaptive capacity of battery pack management in the fuel car oil-to-electricity scenario is improved.

Description

Technical Field

[0001] This invention relates to the field of power battery management technology, and in particular to a vehicle-grade battery pack management system for a platform-based conversion of gasoline vehicles to electric vehicles. Background Technology

[0002] In the conversion of gasoline vehicles to electric vehicles, the power battery packs often need to be adapted and installed on different vehicle platforms due to limitations in the original vehicle chassis structure, layout space, vehicle control architecture and wiring harness interface conditions, resulting in significant differences in their operating environment.

[0003] Existing battery management systems are mostly developed for pure electric vehicles, typically setting thresholds and configuring control strategies based on relatively fixed vehicle parameters, thermal environment boundaries, and load characteristics. This makes them difficult to directly apply to vehicles converted from gasoline to electric. Especially in converted vehicles, the original vehicle's CAN bus signal types, sampling accuracy, and communication cycles are inconsistent. Furthermore, different vehicle models have significant differences in curb weight, drive requirements, heat dissipation conditions, and battery compartment layouts, resulting in strong dispersion in the load level, temperature rise rate, and individual cell consistency changes of the battery pack during charging and discharging.

[0004] Most existing solutions adopt centralized static monitoring and fixed threshold management, which do not make sufficient use of the correlation between vehicle driving status, cell status and vehicle platform parameters. It is difficult to switch thermal management, power limiting and equalization path in a timely manner according to load changes. After executing relevant controls, there is also a lack of a continuous tracking and feedback correction mechanism for changes in the timing of operating status. It is impossible to dynamically optimize management thresholds and control strategies for different vehicle models and different operating conditions, resulting in weak adaptability of battery pack management in the scenario of converting fuel vehicles to electric vehicles. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a vehicle-grade battery pack management system for converting gasoline vehicles to electric platforms. The system includes: Distributed cell acquisition module, vehicle interactive communication module, multi-model parameter database storage module, main control module, thermal management linkage control module, and active balancing drive module; The distributed cell acquisition module is used to periodically acquire the operating status data of individual cells; The vehicle interactive communication module is used to collect vehicle driving status signals from the original vehicle's CAN bus. The multi-vehicle model parameter database storage module is used to automatically match the corresponding target vehicle platform parameters based on the input vehicle model code; The main control module is used to: calculate the comprehensive battery load characterization value for the current cycle based on the operating status data, the vehicle driving status signal, and the target vehicle platform parameters; If the comprehensive battery load characterization value is greater than the dynamic load threshold, the system is determined to be in a high load state, and a first control command is generated and sent to the vehicle interactive communication module to perform dynamic limiting of output power and to the thermal management linkage control module to perform graded thermal management adjustment. If the comprehensive battery load characterization value is less than or equal to the dynamic load threshold, the system is determined to be in normal operation state, and a second control command is generated and sent to the active balancing drive module to perform single-cell active balancing processing based on cell voltage difference. The main control module is also used to monitor the temporal change characteristics of the running status data after executing the corresponding processing path within a preset period, adaptively adjust the dynamic load threshold based on the temporal change characteristics, and perform feedback adjustment and re-determination for the next period based on the adjusted dynamic load threshold.

[0006] Furthermore: The operating status data includes individual cell voltage and cell temperature; The vehicle driving status signals include throttle opening and vehicle speed signals; The target vehicle platform parameters include chassis load parameters and transmission ratio parameters; The comprehensive battery load characterization value is determined based on the operating status data, the vehicle driving status signal, and the target vehicle platform parameters, specifically including: The main control module calculates the voltage drop rate of the individual cell and the temperature rise gradient of the cell. Based on the throttle opening, the vehicle speed signal, the chassis load parameters, and the transmission ratio parameters, the instantaneous power demand of the vehicle is calculated. The voltage drop rate, the temperature rise gradient, and the instantaneous power demand of the vehicle are fused together to obtain the comprehensive battery load characterization value, and the comprehensive battery load characterization value is positively correlated with both the temperature rise gradient and the instantaneous power demand of the vehicle.

[0007] Furthermore: The vehicle interactive communication module acquires the braking signal from the original vehicle's CAN bus; The dynamic output power limit is determined based on the deviation between the comprehensive battery load characterization value and the dynamic load threshold, specifically including: The deviation magnitude is calculated, and a target power limitation factor is calculated based on the deviation magnitude; the target power limitation factor is negatively correlated with the deviation magnitude. The maximum output power of the battery pack is dynamically limited based on the braking intensity level of the braking signal and the target power limiting coefficient.

[0008] Furthermore: The thermal management linkage control module obtains the current charging and discharging power; The graded thermal management adjustment is determined based on the cell temperature in the operating status data, and specifically includes: The average temperature of the battery cell is calculated based on the cell temperature, and the deviation index between the average temperature of the battery cell and the preset safe temperature range is calculated. Based on the deviation index and the charging / discharging power, the water cooling flow rate or PTC heating power is adjusted in stages using a multi-level dynamic temperature control strategy. When the deviation index represents a high-temperature deviation and the degree of deviation increases, the water cooling flow rate is increased in a positive correlation; when the deviation index represents a low-temperature deviation and the degree of deviation increases, the PTC heating power is increased in a positive correlation.

[0009] Furthermore: The active equalization drive module adopts a bidirectional DC-DC equalization circuit. The single-cell active equalization process is determined based on the global cell voltage difference characterization value, and specifically includes: The global cell voltage difference characterization value is extracted based on the individual cell voltage of each cell, and the global cell voltage difference characterization value is compared with a preset equalization trigger threshold. If the global cell voltage difference characterization value is greater than the equalization trigger threshold, the bidirectional DC-DC equalization circuit is activated, and a preset equalization current is output for active equalization until the global cell voltage difference characterization value drops to within the preset equalization stop threshold. The equalization trigger threshold is 50mV, the preset equalization current is 2A, and the equalization stop threshold is 10mV.

[0010] Furthermore: The dynamic load threshold includes a base threshold and an adaptive floating compensation amount; The adaptive adjustment of the dynamic load threshold is determined based on the time-series variation characteristics, specifically including: Within the preset period, high-frequency fluctuation features and mean drift features are extracted from the time-series change features, and a system aging characterization index is constructed based on the high-frequency fluctuation features and the mean drift features. When the system aging characterization index increases, the adaptive floating compensation amount is reduced according to the negative correlation.

[0011] Furthermore, the feedback adjustment and the re-determination of the next cycle are determined based on the updated comprehensive battery load characterization value calculated from the updated operating status data, specifically including: The updated comprehensive battery load characterization value is compared with the adjusted dynamic load threshold a second time. If the updated comprehensive battery load characterization value is still greater than the adjusted dynamic load threshold, a degraded operation control command is generated to forcibly limit the system output power and increase the monitoring frequency of the time-series change characteristics in the next cycle.

[0012] Furthermore: The multi-vehicle parameter database storage module has a built-in erasable and rewritable storage chip. The target vehicle platform parameters are determined based on the matching result of the vehicle code in the underlying logical mapping table, specifically including: The vehicle model code is parsed in the underlying logic mapping table to retrieve the corresponding voltage protection basic threshold parameters; The chassis load parameters, the transmission ratio parameters, and the voltage protection basic threshold parameters are aggregated to generate the target vehicle platform parameters, which are then output to the main control module as the reference data for initializing the dynamic load threshold.

[0013] Furthermore: The distributed cell acquisition module includes multiple independent acquisition channels, and each acquisition channel independently corresponds to a string of cells. The operating status data is determined based on the initial acquisition data obtained by the acquisition channel, and specifically includes: The initial voltage and initial temperature data of each battery cell are acquired at a preset sampling frequency. The initial voltage data is filtered and calibrated by a built-in hardware filtering module, and the final operating status data is output with an acquisition accuracy of ±1mV, eliminating electromagnetic interference errors during platform switching.

[0014] Furthermore: When the thermal management linkage control module increases the water cooling flow rate in a positive correlation, it calculates the current heat dissipation redundancy coefficient and feeds the heat dissipation redundancy coefficient back to the vehicle interaction communication module. The vehicle communication module dynamically corrects the maximum output power limit boundary of the battery pack based on the heat dissipation redundancy coefficient; when the heat dissipation redundancy coefficient increases, the maximum output power limit boundary is increased in a positive correlation, thereby achieving coordinated release of vehicle power and thermal balance.

[0015] This invention collects the operating status data of individual battery cells through a distributed cell acquisition module, and combines this with vehicle driving status signals collected by the vehicle interaction communication module and target vehicle platform parameters matched by a multi-vehicle parameter database storage module. This enables a comprehensive characterization of the differences between the battery pack's operating conditions and the vehicle platform, improving the adaptability of battery pack status identification in the context of converting gasoline vehicles to electric vehicles. The main control module determines high-load and normal operating states based on the comprehensive battery load characterization value and dynamic load threshold, and simultaneously executes dynamic output power limiting, graded thermal management adjustment, and active cell balancing based on cell voltage difference. This achieves differentiated control for different load states, improving the responsiveness of battery pack management strategies in the context of converting gasoline vehicles to electric vehicles. Furthermore, the main control module monitors the temporal change characteristics of the operating status data after executing the corresponding processing path, and adaptively adjusts the dynamic load threshold based on these temporal change characteristics. This enables feedback correction of the management threshold and re-judgment for the next cycle, improving the adaptive adjustment capability of battery pack management in the context of converting gasoline vehicles to electric vehicles.

[0016] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0017] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of the invention. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A block diagram of an automotive-grade battery pack management system for a gasoline vehicle converted to electric platform, according to an embodiment of the present invention, is shown. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Furthermore, the terms "and / or" in this article are merely a description of the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0020] Figure 1 A block diagram of an automotive-grade battery pack management system for converting gasoline vehicles to electric platforms, according to an embodiment of the present invention, is shown. The system includes: The system includes a distributed battery cell acquisition module 101, a vehicle interactive communication module 102, a multi-model parameter database storage module 103, a main control module 104, a thermal management linkage control module 105, and an active balancing drive module 106. The distributed cell acquisition module is used to periodically acquire the operating status data of individual cells; The vehicle interactive communication module is used to collect vehicle driving status signals from the original vehicle's CAN bus. The multi-vehicle model parameter database storage module is used to automatically match the corresponding target vehicle platform parameters based on the input vehicle model code; The main control module is used to: calculate the comprehensive battery load characterization value for the current cycle based on the operating status data, the vehicle driving status signal, and the target vehicle platform parameters; If the comprehensive battery load characterization value is greater than the dynamic load threshold, the system is determined to be in a high load state, and a first control command is generated and sent to the vehicle interactive communication module to perform dynamic limiting of output power and to the thermal management linkage control module to perform graded thermal management adjustment. If the comprehensive battery load characterization value is less than or equal to the dynamic load threshold, the system is determined to be in normal operation state, and a second control command is generated and sent to the active balancing drive module to perform single-cell active balancing processing based on cell voltage difference. The main control module is also used to monitor the temporal change characteristics of the running status data after executing the corresponding processing path within a preset period, adaptively adjust the dynamic load threshold based on the temporal change characteristics, and perform feedback adjustment and re-determination for the next period based on the adjusted dynamic load threshold.

[0021] In some embodiments, the operating status data includes individual cell voltage and cell temperature; the vehicle driving status signal includes throttle opening and vehicle speed signal; the target vehicle platform parameters include chassis load parameters and transmission ratio parameters; the comprehensive battery load characterization value is determined based on the operating status data, the vehicle driving status signal, and the target vehicle platform parameters, specifically including: the main control module calculates the voltage drop rate of the individual cell voltage and the temperature rise gradient of the cell temperature; based on the throttle opening, the vehicle speed signal, the chassis load parameters, and the transmission ratio parameters, calculates the instantaneous power demand of the entire vehicle; and fuses the voltage drop rate, the temperature rise gradient, and the instantaneous power demand of the entire vehicle to obtain the comprehensive battery load characterization value, and the comprehensive battery load characterization value is positively correlated with both the temperature rise gradient and the instantaneous power demand of the entire vehicle. According to embodiments of the present invention, by fusing the voltage drop rate, temperature rise gradient, and instantaneous power demand of the entire vehicle to calculate the comprehensive battery load characterization value, a precise quantitative characterization of multi-dimensional battery load status is achieved, improving the system's accuracy in identifying the actual operating load of the battery.

[0022] For example, under rapid acceleration conditions in a certain converted electric SUV, the main control module detects that the individual cell voltage drops from 3.86V in the previous second to 3.85V in the current second, and calculates the voltage drop rate V. drop The value is 10mV / s; the cell temperature rises from 35.0℃ to 35.5℃, and the temperature rise gradient T is calculated. grad The speed is 0.5℃ / s; the throttle opening A is obtained. acc The vehicle speed signal V is 80% (i.e., 0.8). veh The vehicle's instantaneous power demand is 60 km / h, chassis load factor M is 1500 kg, and transmission ratio i0 is 8.0. Where K1 is the first preset dimension conversion coefficient, with a value of 1000 (unit: kg⋅(km / h)). Substituting the data, the instantaneous power demand P of the whole vehicle is calculated. req =9.0; Comprehensive battery load characterization value L batt =ω1⋅V drop +ω2⋅T grad +ω3⋅P req Where ω1 is the voltage drop weighting coefficient (taken as 0.5s / mV), ω2 is the temperature rise weighting coefficient (taken as 10s / ℃), and ω3 is the power demand weighting coefficient (taken as 1.0). Substituting the data, the comprehensive battery load characterization value L is calculated. batt =19.0.

[0023] In other embodiments, the main control module performs synchronous time processing on the operating status data and the vehicle driving status signal according to a preset sampling period, and calculates the comprehensive battery load characterization value based on the time-synchronized data; the voltage drop rate is obtained by dividing the difference between the average cell voltage of the current period and the average cell voltage of the previous period by the preset sampling period; the temperature rise gradient is obtained by dividing the difference between the highest cell temperature or the average cell temperature of the current period and the corresponding temperature of the previous period by the preset sampling period; the instantaneous power demand of the vehicle is calculated by converting the throttle opening, the vehicle speed signal, the chassis load parameters, and the transmission ratio parameters through a preset calibration relationship; wherein, the preset calibration relationship is determined by the calibration table corresponding to the platform parameters of the target vehicle model, which is used to ensure that the comprehensive battery load characterization value under different vehicle models has uniform comparability, so that the main control module can stably perform high load judgment or normal operation judgment accordingly.

[0024] In some embodiments, the vehicle communication module acquires the braking signal from the original vehicle's CAN bus; the dynamic output power limitation is determined based on the deviation range between the comprehensive battery load characterization value and the dynamic load threshold, specifically including: calculating the deviation range and calculating a target power limitation coefficient based on the deviation range; the target power limitation coefficient is negatively correlated with the deviation range; and dynamically limiting the maximum output power of the battery pack according to the braking intensity level of the braking signal and the target power limitation coefficient, so as to suppress the continued rise of the comprehensive battery load characterization value while ensuring the braking safety of the original vehicle. According to the embodiments of the present invention, by combining the deviation range and the braking intensity to dynamically limit the maximum output power of the battery, a graded and refined control of power limitation under high load conditions is achieved, improving the safety of system operation and the reliability of braking response.

[0025] For example, suppose the current system presets the dynamic load threshold L. th The value is 15.0. Since the comprehensive battery load characterization value Lbatt is 19.0, the system is determined to be in a high load state, and the deviation amplitude ΔL = L batt -L th =4.0; Target power limitation factor C limit =1−K2⋅ΔL; where K2 is the limiting adjustment sensitivity coefficient, with a value of 0.05. Substituting this into the calculation yields C. limit =0.8; simultaneously, the vehicle interactive communication module acquires the braking signal and parses out the braking intensity level B. level Level 2 (corresponding to the safety-limited power attenuation factor λ) brake (0.9), if the rated maximum output power P of the battery pack nom If the power is 100kW, then the maximum output power P after dynamic limiting is... max_out =P nom ⋅Climit ⋅λ brake Substituting the data, we get P. max_out =72kW, thus dynamically limiting the maximum output power from 100kW to 72kW, effectively suppressing the continued increase of battery load.

[0026] In other embodiments, the vehicle communication module classifies the braking signal obtained from the original vehicle CAN bus into levels, and classifies the braking intensity into at least one of braking not triggered, light braking, moderate braking, and heavy braking; the main control module first determines the deviation range based on the difference between the comprehensive battery load characterization value and the dynamic load threshold, and then outputs the target power limiting coefficient according to the preset power limiting mapping relationship, and limits the target power limiting coefficient within a preset safety range to avoid excessive power limiting range leading to sudden changes in vehicle power; when the braking signal characterizes an increase in braking intensity, the vehicle communication module prioritizes meeting the power boundary requirements corresponding to braking safety, and on this basis, dynamically corrects the maximum output power of the battery pack, so that the output power limiting process takes into account both battery protection and original vehicle braking safety.

[0027] In some embodiments, the thermal management linkage control module acquires the current charge / discharge power; the graded thermal management adjustment is determined based on the cell temperature in the operating status data, specifically including: calculating the average cell temperature in combination with the cell temperature, and calculating the deviation index between the average cell temperature and a preset safe temperature range; adjusting the water cooling flow rate or PTC heating power in stages according to the deviation index and the charge / discharge power through a multi-level dynamic temperature control strategy; when the deviation index indicates a high-temperature deviation and the degree of deviation increases, increasing the water cooling flow rate according to a positive correlation; when the deviation index indicates a low-temperature deviation and the degree of deviation increases, increasing the PTC heating power according to a positive correlation. According to embodiments of the present invention, by using a multi-level dynamic temperature control strategy based on the cell temperature deviation index and the charge / discharge power, graded linkage adjustment of water cooling and PTC heating is achieved, improving the response speed and temperature control accuracy of battery pack temperature control.

[0028] For example, under the aforementioned high-load operating conditions, the thermal management linkage control module obtains the current charging and discharging power P of the battery pack. cd For a power of 50kW, the temperature of all individual cells was collected, and the average cell temperature T was calculated. avg The set temperature is 38℃, and the preset safe temperature range is [T]. safe_min ,T safe_max ], that is, [20℃, 35℃], when T avg >T safe_max At that time, the high temperature deviation index To address this high temperature deviation, the water cooling flow rate... Among them, Qbase The base water cooling flow rate is set at 5.0 L / min; K3 is the flow gain coefficient, set at 0.5 L / (min·kW). Substituting these values, the target water cooling flow rate Q is obtained. cool =7.15L / min. It can be seen that when the high temperature deviates from the index D... temp When the flow rate is increased, the water cooling flow rate is significantly improved in a positive correlation to enhance heat dissipation.

[0029] In other embodiments, the thermal management linkage control module calculates the average temperature of the battery cells based on the temperature data of each battery cell uploaded by the distributed battery cell acquisition module, and compares the average temperature of the battery cells with the upper and lower limits of a preset safe temperature range to determine whether the current temperature is in a high-temperature deviation state, a low-temperature deviation state, or a normal temperature state. When the average temperature of the battery cells is higher than the upper limit of the preset safe temperature range, the water cooling flow rate is increased according to a preset gain relationship. When the average temperature of the battery cells is lower than the lower limit of the preset safe temperature range, the PTC heating power is increased according to a preset gain relationship. When the average temperature of the battery cells is within the preset safe temperature range, the basic thermal management output level is maintained. The multi-level dynamic temperature control strategy includes at least a basic level, an enhanced level, and a forced protection level, so that the thermal management linkage control module can perform graded temperature control according to the degree of temperature deviation and the magnitude of the charging and discharging power.

[0030] In some embodiments, the active balancing drive module employs a bidirectional DC-DC balancing circuit. The single-cell active balancing process is determined based on the global cell voltage difference characterization value, specifically including: extracting the global cell voltage difference characterization value based on the single-cell voltage of each individual battery cell, and comparing the global cell voltage difference characterization value with a preset balancing trigger threshold; if the global cell voltage difference characterization value is greater than the balancing trigger threshold, the bidirectional DC-DC balancing circuit is activated, and a preset balancing current is output for active balancing until the global cell voltage difference characterization value drops below a preset balancing stop threshold; wherein, the balancing trigger threshold is 50mV, the preset balancing current is 2A, and the balancing stop threshold is 10mV. According to the embodiments of the present invention, active balancing control based on the global cell voltage difference characterization value through the bidirectional DC-DC balancing circuit achieves rapid and effective elimination of voltage differences between cells, improving the overall capacity utilization and cycle life of the battery pack.

[0031] For example, when the comprehensive battery load characterization value is less than or equal to the dynamic load threshold (e.g., when the vehicle is cruising at a low speed, L...), batt When the voltage is 12.0, it is determined to be in normal operating condition. The main control module extracts the individual cell voltages of each battery cell, where the highest individual cell voltage U... max It is 3.88V, the lowest single-unit voltage U minThe global cell voltage difference characterization value ΔU is 3.82V. global =U max -U min =60mV > equalization trigger threshold 50mV, the active equalization drive module activates the bidirectional DC-DC equalization circuit, transferring energy from the 3.88V high-voltage cell to the 3.82V low-voltage cell, and outputs the preset equalization current 2A. This process continues until ΔU is detected. global When the voltage drops to 8mV, the system shuts down the bidirectional DC-DC equalization circuit.

[0032] In other embodiments, the active balancing drive module calculates the global cell voltage difference characterization value based on the individual cell voltages of each battery cell. The global cell voltage difference characterization value is the difference between the individual cell voltage of the highest voltage battery cell and the individual cell voltage of the lowest voltage battery cell. When the global cell voltage difference characterization value is greater than the balancing trigger threshold, the active balancing drive module identifies the high-voltage cells to be discharged and the low-voltage cells to be replenished, and drives the bidirectional DC-DC balancing circuit to transfer energy according to a preset balancing current. During the balancing process, the distributed cell acquisition module continuously feeds back the individual cell voltage and cell temperature of each battery cell. If any battery cell voltage or temperature exceeds the limit, or the global cell voltage difference characterization value drops below the balancing stop threshold, the bidirectional DC-DC balancing circuit is shut down to ensure that the active balancing process has clear start conditions, execution paths, and stop conditions.

[0033] In some embodiments, the dynamic load threshold includes a base threshold and an adaptive floating compensation amount; the adaptive adjustment of the dynamic load threshold is determined based on the time-series variation characteristics, specifically including: extracting high-frequency fluctuation characteristics and mean drift characteristics from the time-series variation characteristics within the preset period, and constructing a system aging characterization index based on the high-frequency fluctuation characteristics and the mean drift characteristics; when the system aging characterization index increases, reducing the adaptive floating compensation amount according to a negative correlation, so as to dynamically reduce the dynamic load threshold. According to the embodiments of the present invention, by extracting high-frequency fluctuation and mean drift characteristics to construct a system aging characterization index, adaptive floating compensation adjustment of the dynamic load threshold is realized, improving the system's adaptive adaptability to battery aging state.

[0034] For example, setting the dynamic load threshold L th The basic threshold L base The upper limit of the adaptive floating compensation amount C in the initial state is 12.0. max The value is 4.0. Within a preset period (e.g., 1000 operating hours), the high-frequency fluctuation characteristic value F, which characterizes the increase in internal resistance, is extracted from the time-series variation characteristics of the individual unit voltage. fluct The value is 0.15, and the mean shift eigenvalue F, which characterizes capacity decay, is...drift The aging characterization index I is 0.2. aging =μ1⋅F fluct +μ2⋅F drift Where μ1 is the fluctuation weight (value 10) and μ2 is the drift weight (value 5), substituting the data yields I. aging =2.5; Adaptive floating compensation amount C comp =C max −K4⋅I aging Where K4 is the aging compensation attenuation coefficient, with a value of 0.8, substituting it into the calculation yields Ccomp = 2.0. At this point, the adjusted dynamic load threshold L... th =L base +C comp =14.0.

[0035] In other embodiments, the main control module extracts the time-series change features according to a sliding time window within the preset period, and uses the fluctuation information of single cell voltage, cell temperature, and the comprehensive battery load characterization value as inputs for the high-frequency fluctuation features, and uses the long-term decreasing trend of single cell voltage, the changing trend of capacity utilization rate, or the changing trend of temperature rise baseline as inputs for the mean drift features; the system aging characterization index is obtained by weighted calculation of the high-frequency fluctuation features and the mean drift features, and the adaptive floating compensation amount is updated between a preset upper limit value and a preset lower limit value; the dynamic load threshold is obtained by superimposing the base threshold and the adaptive floating compensation amount. When the system aging characterization index increases, the adaptive floating compensation amount decreases, so that the dynamic load threshold decreases synchronously, thereby enabling the aged battery pack to enter the protection control path earlier.

[0036] In some embodiments, the feedback adjustment and re-determination of the next cycle are determined based on the updated comprehensive battery load characterization value calculated from the updated operating status data. Specifically, this includes: comparing the updated comprehensive battery load characterization value with the adjusted dynamic load threshold a second time; if the updated comprehensive battery load characterization value is still greater than the adjusted dynamic load threshold, a degraded operation control command is generated to forcibly limit the system output power and increase the monitoring frequency of the time-series change characteristics in the next cycle. According to embodiments of the present invention, by comparing the updated comprehensive battery load characterization value a second time and generating a degraded operation command, forced protection and increased monitoring frequency under continuous high load conditions are achieved, thereby improving the reliability of system operation and fault early warning capabilities.

[0037] For example, after completing the adaptive adjustment of the dynamic load threshold (the threshold is updated to 14.0) and entering the next control cycle, based on the updated single-cell voltage drop rate and cell temperature rise gradient, the current updated comprehensive battery load characterization value of 14.5 is calculated to be greater than 14.0, indicating that the pre-set power limiting and thermal management have failed to completely curb load deterioration. At this time, the main control module generates a degraded operation control command: forcibly reducing the maximum output power of the system by 50% on the basis of the aforementioned 72kW, that is, forcibly limiting it to within 36kW; at the same time, the sampling and monitoring frequency of the time-series change characteristics of the operating status data in the next cycle is increased from the conventional 10Hz to 50Hz, so as to more precisely intercept potential thermal runaway risks.

[0038] In other embodiments, when the main control module performs the feedback adjustment and the re-determination of the next cycle, it uses the operating status data re-collected in the current cycle, the vehicle driving status signal, and the updated dynamic load threshold as secondary determination inputs. When the updated comprehensive battery load characterization value is still greater than the adjusted dynamic load threshold, the degraded operation control command includes at least one of reducing the maximum output power limit, increasing the sampling frequency of time-series change characteristics, and shortening the next threshold update cycle. When the updated comprehensive battery load characterization value falls below the adjusted dynamic load threshold and continues to reach the preset recovery time, the main control module releases the degraded operation control command or restores the system output capability step by step, so that the feedback adjustment process has a closed-loop recovery mechanism.

[0039] In some embodiments, the multi-vehicle parameter database storage module has a built-in erasable and rewritable storage chip; the target vehicle platform parameters are determined based on the matching result of the vehicle code in the underlying logical mapping table, specifically including: parsing the vehicle code in the underlying logical mapping table, retrieving the corresponding voltage protection basic threshold parameter; aggregating the chassis load parameter, the transmission ratio parameter, and the voltage protection basic threshold parameter to generate the target vehicle platform parameters, and outputting them to the main control module as the reference data for the initialization of the dynamic load threshold. According to the embodiments of the present invention, by matching the vehicle code and aggregating multi-dimensional platform parameters through the underlying logical mapping table, the rapid generation of target vehicle platform parameters and the initialization of dynamic load thresholds are achieved, improving the efficiency and accuracy of system platform adaptation.

[0040] For example, during the system factory adaptation phase, technicians input the vehicle model code PLAT-A-2023, representing a certain fuel-powered Class A sedan chassis platform, into the system. After receiving this code, the built-in erasable and rewritable memory chip of the multi-vehicle parameter database storage module searches in the underlying logic mapping table and retrieves the voltage protection basic threshold parameter V specific to that vehicle model. prot_baseThe voltage is 3.0V. Simultaneously, the inherent chassis load parameter M (1350kg) and transmission ratio parameter i0 (7.5) of this vehicle model are extracted from the mapping table. These three parameters are then encapsulated and aggregated to generate the target vehicle platform parameter data package: {Model:PLAT-A-2023,M:1350,i0:7.5,V} prot_base The data packet is sent directly to the main control module. After parsing the data packet, the main control module uses 3.0V as the reference data for calculating the safe lower limit of the dynamic load threshold, thereby realizing automatic adaptation of chassis parameters of different oil-to-electric vehicle models without writing code.

[0041] In other embodiments, the underlying logic mapping table pre-stores the correspondence between vehicle model codes and chassis load parameters, transmission ratio parameters, voltage protection basic threshold parameters, and thermal management calibration parameters. After receiving the vehicle model code, the multi-vehicle model parameter database storage module first performs code format verification and legality verification, and then retrieves and outputs the target vehicle model platform parameters corresponding to the vehicle model code. If the retrieval is successful, the target vehicle model platform parameters are sent to the main control module to complete the dynamic load threshold initialization. If the retrieval fails, preset general protection parameters are called as default initialization parameters to ensure that the system can still enter an executable safety control mode when no specific vehicle model data is matched.

[0042] In some embodiments, the distributed cell acquisition module includes multiple independent acquisition channels, each corresponding independently to a string of cells. The operating status data is determined based on the initial acquisition data obtained by the acquisition channels, specifically including: acquiring initial voltage and initial temperature data of each string of cells at a preset sampling frequency; filtering and calibrating the initial voltage data through a built-in hardware filtering module to output the final operating status data with an acquisition accuracy of ±1mV, thereby eliminating electromagnetic interference errors during platform switching. According to embodiments of the present invention, multi-channel independent acquisition and hardware filtering calibration achieve ±1mV high-precision data output, effectively eliminating electromagnetic interference errors during platform switching, and improving the accuracy and anti-interference capability of cell status data acquisition.

[0043] For example, for a power battery pack modified from a gasoline vehicle chassis and containing 96 battery cells, the distributed cell acquisition module physically sets up 96 independent acquisition channels. Among them, the 12th acquisition channel corresponds independently to the 12th battery cell via a dedicated wiring harness. Under the strong electromagnetic interference environment of the vehicle's high-power motor starting, the 12th acquisition channel acquires the initial voltage data at a preset sampling frequency of 1kHz. At this time, the measured original voltage is 3.825V, but it is superimposed with high-frequency electromagnetic noise with an amplitude of about ±20mV. The initial voltage data is filtered and calibrated by the built-in hardware filtering module (such as an RC low-pass filter circuit combined with a Kalman digital filter algorithm) to filter out the noise interference components and finally output the stable operating status data of 3.825V. Through calibration verification, the error between the voltage value output by the module and the actual chemical voltage of the battery cell is strictly controlled within the acquisition accuracy of ±1mV, effectively eliminating the electromagnetic interference error caused by the modification of the chassis electrical architecture.

[0044] In other embodiments, the distributed cell acquisition module acquires the initial voltage and initial temperature data of each string of cells at a preset sampling frequency, and performs channel number binding, timestamp marking, and outlier removal processing on the data uploaded by each acquisition channel. The hardware filtering module performs a combination of analog and digital filtering calibration on the initial voltage data to suppress common-mode interference and high-frequency spike noise introduced by motor starting, current surges, or chassis modification wiring. The filtered and calibrated voltage and temperature data are encapsulated as the operating status data and sent to the main control module. When any acquisition channel experiences a disconnection, drift exceeding limits, or abnormal acquisition accuracy, the distributed cell acquisition module outputs a corresponding fault identifier for the main control module to perform data shielding or fault protection in subsequent judgments.

[0045] In some embodiments, when the thermal management linkage control module increases the water cooling flow rate in a positive correlation, it calculates the current heat dissipation redundancy coefficient and feeds it back to the vehicle interaction communication module. The vehicle interaction communication module dynamically corrects the maximum output power limit boundary of the battery pack based on the heat dissipation redundancy coefficient. When the heat dissipation redundancy coefficient increases, the maximum output power limit boundary is increased in a positive correlation, thereby achieving coordinated release of vehicle power and thermal balance. According to embodiments of the present invention, by dynamically correcting the maximum output power limit boundary through heat dissipation redundancy coefficient feedback, coordinated optimization of vehicle power performance and thermal balance is achieved, improving the safety of battery pack power output and power utilization efficiency.

[0046] For example, when the thermal management linkage control module controls the water cooling flow rate Q cool When the flow rate is increased to 7.15 L / min, the maximum design displacement (i.e., the theoretical maximum heat dissipation capacity) of the current water pump is read as Q. max_coolThe flow rate is 15.0 L / min, and the heat dissipation redundancy factor R cool =(Q max_cool -Q cool ) / Q max_cool The main control module feeds back this coefficient of 0.523 to the vehicle communication module, setting the maximum output power limit boundary P. limit_bound =P base_bound ⋅(1+K5⋅R cool ); where P base_bound Given the basic safety power boundary (set to 80kW), K5 is the redundancy release gain coefficient (valued at 0.4), and substituting the data, P is calculated. limit_bound ≈96.7kW.

[0047] In other embodiments, the thermal management linkage control module calculates the heat dissipation redundancy coefficient based on the current water cooling flow rate and the maximum designed heat dissipation capacity of the cooling system, and sends the heat dissipation redundancy coefficient to the main control module or the vehicle interaction communication module. When the vehicle interaction communication module corrects the maximum output power limit boundary of the battery pack based on the heat dissipation redundancy coefficient, it uses the current thermal management capability improvement as the release basis, and simultaneously satisfies the joint constraints of the rated maximum output power limit, the braking safety power boundary, and the battery protection power boundary. When the heat dissipation redundancy coefficient increases, the maximum output power limit boundary is allowed to be moderately increased within the joint constraint range. When the heat dissipation redundancy coefficient decreases, the maximum output power limit boundary is reduced to achieve coordinated matching of power output capability and thermal safety capability.

[0048] It should be understood that the various processes described above can be used to rearrange, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0049] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A vehicle-grade battery pack management system for converting gasoline vehicles to electric platforms, characterized in that, include: Distributed cell acquisition module, vehicle interactive communication module, multi-model parameter database storage module, main control module, thermal management linkage control module, and active balancing drive module; The distributed cell acquisition module is used to periodically acquire the operating status data of individual cells; The vehicle interactive communication module is used to collect vehicle driving status signals from the original vehicle's CAN bus. The multi-vehicle model parameter database storage module is used to automatically match the corresponding target vehicle platform parameters based on the input vehicle model code; The main control module is used to: calculate the comprehensive battery load characterization value for the current cycle based on the operating status data, the vehicle driving status signal, and the target vehicle platform parameters; If the comprehensive battery load characterization value is greater than the dynamic load threshold, the system is determined to be in a high load state, and a first control command is generated and sent to the vehicle interactive communication module to perform dynamic limiting of output power and to the thermal management linkage control module to perform graded thermal management adjustment. If the comprehensive battery load characterization value is less than or equal to the dynamic load threshold, the system is determined to be in normal operation state, and a second control command is generated and sent to the active balancing drive module to perform single-cell active balancing processing based on cell voltage difference. The main control module is also used to monitor the temporal change characteristics of the running status data after executing the corresponding processing path within a preset period, adaptively adjust the dynamic load threshold based on the temporal change characteristics, and perform feedback adjustment and re-determination for the next period based on the adjusted dynamic load threshold.

2. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 1, characterized in that: The operating status data includes individual cell voltage and cell temperature; The vehicle driving status signals include throttle opening and vehicle speed signals; The target vehicle platform parameters include chassis load parameters and transmission ratio parameters; The comprehensive battery load characterization value is determined based on the operating status data, the vehicle driving status signal, and the target vehicle platform parameters, specifically including: The main control module calculates the voltage drop rate of the individual cell and the temperature rise gradient of the cell. Based on the throttle opening, the vehicle speed signal, the chassis load parameters, and the transmission ratio parameters, the instantaneous power demand of the vehicle is calculated. The voltage drop rate, the temperature rise gradient, and the instantaneous power demand of the vehicle are fused together to obtain the comprehensive battery load characterization value, and the comprehensive battery load characterization value is positively correlated with both the temperature rise gradient and the instantaneous power demand of the vehicle.

3. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 2, characterized in that: The vehicle interactive communication module acquires the braking signal from the original vehicle's CAN bus; The dynamic output power limit is determined based on the deviation between the comprehensive battery load characterization value and the dynamic load threshold, specifically including: The deviation magnitude is calculated, and a target power limitation factor is calculated based on the deviation magnitude; the target power limitation factor is negatively correlated with the deviation magnitude. The maximum output power of the battery pack is dynamically limited based on the braking intensity level of the braking signal and the target power limiting coefficient.

4. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 3, characterized in that: The thermal management linkage control module obtains the current charging and discharging power; The graded thermal management adjustment is determined based on the cell temperature in the operating status data, and specifically includes: The average temperature of the battery cell is calculated based on the cell temperature, and the deviation index between the average temperature of the battery cell and the preset safe temperature range is calculated. Based on the deviation index and the charging / discharging power, the water cooling flow rate or PTC heating power is adjusted in stages using a multi-level dynamic temperature control strategy. When the deviation index represents a high-temperature deviation and the degree of deviation increases, the water cooling flow rate is increased in a positive correlation; when the deviation index represents a low-temperature deviation and the degree of deviation increases, the PTC heating power is increased in a positive correlation.

5. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 4, characterized in that: The active equalization drive module adopts a bidirectional DC-DC equalization circuit. The single-cell active equalization process is determined based on the global cell voltage difference characterization value, and specifically includes: The global cell voltage difference characterization value is extracted based on the individual cell voltage of each cell, and the global cell voltage difference characterization value is compared with a preset equalization trigger threshold. If the global cell voltage difference characterization value is greater than the equalization trigger threshold, the bidirectional DC-DC equalization circuit is activated, and a preset equalization current is output for active equalization until the global cell voltage difference characterization value drops to within the preset equalization stop threshold. The equalization trigger threshold is 50mV, the preset equalization current is 2A, and the equalization stop threshold is 10mV.

6. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 5, characterized in that: The dynamic load threshold includes a base threshold and an adaptive floating compensation amount; The adaptive adjustment of the dynamic load threshold is determined based on the time-series variation characteristics, specifically including: Within the preset period, high-frequency fluctuation features and mean drift features are extracted from the time-series change features, and a system aging characterization index is constructed based on the high-frequency fluctuation features and the mean drift features. When the system aging characterization index increases, the adaptive floating compensation amount is reduced according to the negative correlation.

7. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 6, characterized in that, The feedback adjustment and the re-determination of the next cycle are determined based on the updated comprehensive battery load characterization value calculated from the updated operating status data, specifically including: The updated comprehensive battery load characterization value is compared with the adjusted dynamic load threshold a second time. If the updated comprehensive battery load characterization value is still greater than the adjusted dynamic load threshold, a degraded operation control command is generated to forcibly limit the system output power and increase the monitoring frequency of the time-series change characteristics in the next cycle.

8. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 7, characterized in that: The multi-vehicle parameter database storage module has a built-in erasable and rewritable storage chip. The target vehicle platform parameters are determined based on the matching result of the vehicle code in the underlying logical mapping table, specifically including: The vehicle model code is parsed in the underlying logic mapping table to retrieve the corresponding voltage protection basic threshold parameters; The chassis load parameters, the transmission ratio parameters, and the voltage protection basic threshold parameters are aggregated to generate the target vehicle platform parameters, which are then output to the main control module as the reference data for initializing the dynamic load threshold.

9. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 8, characterized in that: The distributed cell acquisition module includes multiple independent acquisition channels, and each acquisition channel independently corresponds to a string of cells. The operating status data is determined based on the initial acquisition data obtained by the acquisition channel, and specifically includes: The initial voltage and initial temperature data of each battery cell are acquired at a preset sampling frequency. The initial voltage data is filtered and calibrated by a built-in hardware filtering module, and the final operating status data is output with an acquisition accuracy of ±1mV, eliminating electromagnetic interference errors during platform switching.

10. The automotive-grade battery pack management system for fuel-powered vehicle conversion platforms according to claim 9, characterized in that: When the thermal management linkage control module increases the water cooling flow rate in a positive correlation, it calculates the current heat dissipation redundancy coefficient and feeds the heat dissipation redundancy coefficient back to the vehicle interaction communication module. The vehicle communication module dynamically corrects the maximum output power limit boundary of the battery pack based on the heat dissipation redundancy coefficient; when the heat dissipation redundancy coefficient increases, the maximum output power limit boundary is increased in a positive correlation, thereby achieving coordinated release of vehicle power and thermal balance.

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