Multi-source hybrid power and intelligent power management system for special vehicle

Abstract

The invention relates to the technical field of multi-source hybrid power and intelligent power supply management, and discloses a special vehicle-oriented multi-source hybrid power and intelligent power supply management system, which comprises a data acquisition and processing module for acquiring various parameters, setting acquisition frequency, establishing cache and processing data; the identification and monitoring module establishes a working condition and task two-dimensional model, monitors insulation and electromagnetic interference, outputs a result and gives an alarm; the comprehensive regulation and control module calculates a power ratio, generates a charging and discharging threshold value, determines a power supply priority and outputs a regulation and control signal; the path construction module designs main and standby power supply paths, constructs switching conditions and the like; and the loop switching verification module executes switching, detects a loop and feeds back data. Full-process intelligent management and control of power and a power source of the special vehicle are achieved, multi-source power adaptability, power supply continuity and electrical safety are improved, and reliable operation of the vehicle is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of multi-source hybrid power and intelligent power management technology, and more specifically, to a multi-source hybrid power and intelligent power management system for special vehicles. Background Technology

[0002] Special-purpose vehicles (such as engineering vehicles and military / police vehicles) often operate in complex and harsh environments, undertaking high-load and multi-task operations, placing extremely high demands on the reliability, adaptability, safety, and energy efficiency of their power systems. Multi-source hybrid power systems (integrating engine, motor, and auxiliary power) have become the core direction for power upgrades in special-purpose vehicles because they can balance power output and energy-saving needs. Furthermore, their accompanying intelligent power management technology is crucial for ensuring stable system operation.

[0003] However, existing multi-source hybrid power and power management technologies for special vehicles still have many bottlenecks, making it difficult to meet stringent operational requirements. Traditional systems have a single dimension for identifying operating conditions, focusing only on driving status and failing to establish a linkage identification model based on task level. This results in large deviations in feature parameter mapping and an inability to accurately adapt to different operational scenarios. Furthermore, the multi-source power output ratio often adopts a fixed strategy, without dynamically linking real-time parameters such as battery status and load requirements, leading to poor adaptability and low energy efficiency.

[0004] Meanwhile, there are blind spots in electrical safety monitoring, unreasonable data collection points for insulation and electromagnetic interference, and a lack of hierarchical alarm mechanisms, making it difficult to accurately locate faults. The power supply path design lacks redundancy, the switching trigger conditions are rigid, and interference judgment logic is not embedded, making it easy for power supply interruptions to occur during faults. The setting of charging and discharging thresholds and power supply priorities is not linked to key factors such as temperature and battery cycle count, which further affects battery life and power supply stability. Moreover, there is a lack of effective feedback linkage between modules, making it impossible to form a closed-loop management system.

[0005] Therefore, it is necessary to design a multi-source hybrid power and intelligent power management system for special vehicles to solve the problems of inaccurate identification of working conditions and tasks, poor adaptability of power distribution, unintelligent safety monitoring and path switching, and lack of closed-loop management in the existing technology. Summary of the Invention

[0006] In view of this, the present invention proposes a multi-source hybrid power and intelligent power management system for special vehicles, aiming to solve the problems of inaccurate identification of working conditions and tasks, poor adaptability of power distribution, unintelligent safety monitoring and path switching, and lack of closed-loop management in the existing technology.

[0007] This invention proposes a multi-source hybrid power and intelligent power management system for special vehicles, including: a data acquisition and processing module, configured to acquire operating status parameters, load parameters, environmental parameters, and electrical status parameters, set the acquisition frequency, establish a cache unit, and filter and complete invalid data; The identification and monitoring module is configured to establish a dual-dimensional identification model of working conditions and tasks, complete feature parameter mapping, real-time parameter updates and historical data comparison, and simultaneously select monitoring points to collect insulation and electromagnetic interference data. After comparing with preset thresholds, it outputs identification results and abnormal alarm signals. The integrated control module is configured to receive the identification results, calculate the power output ratio by combining battery and auxiliary energy parameters, generate charge and discharge thresholds based on temperature and battery cycle count, determine power supply priority according to load parameters and task level, and output control signals. The path construction module is configured to design primary and backup power supply paths, establish path switching trigger conditions, embed electromagnetic interference judgment logic, and store path connection parameters and drawings. The circuit switching verification module is configured to receive abnormal alarm signals and control signals, perform main and backup circuit switching after verifying the switching conditions, detect the conduction status of the target circuit, record the switching data, and feed the results back to the data acquisition and processing module and the integrated control module.

[0008] Furthermore, when the identification and monitoring module is configured to establish a dual-dimensional identification model of working conditions and tasks, it includes: the identification and monitoring module is also configured to select start-stop frequency, load fluctuation amplitude, and driving speed as working condition characteristic parameters, and select job type, job duration, and load demand as task characteristic parameters; The identification and monitoring module is also configured to divide the operating condition range, which is divided into stable operating condition, fluctuating operating condition, and impact operating condition according to the combination of start and stop frequency and load fluctuation amplitude, and into low speed operating condition, medium speed operating condition, and high speed operating condition according to driving speed. The identification and monitoring module is also configured to classify tasks into five levels based on the combination of job complexity and load requirements. The higher the level, the higher the job complexity and the greater the load requirements. The identification and monitoring module is also configured to establish a mapping table between working condition characteristic parameters and task levels, and to clarify the adaptation characteristic thresholds for each task level under different working condition ranges.

[0009] Furthermore, when the identification and monitoring module is configured to complete real-time parameter updates and historical data comparison, it includes: the identification and monitoring module is also configured to set a dual-trigger update mechanism, first determining whether the vehicle is in operation; if in operation, triggering model parameter updates according to mileage intervals; if in non-operation, triggering updates according to time intervals, and the update frequency in operation is higher than in non-operation. The identification and monitoring module is also configured to call the working condition and task matching data in the historical operation database, first determine whether the operation scenario corresponding to the retrieved historical data is consistent with the current scenario; if consistent, directly calculate the similarity coefficient between the real-time feature parameters and the historical data; if inconsistent, filter out the historical data with a scenario matching degree higher than the preset matching degree threshold, and then calculate the similarity coefficient. The identification and monitoring module is also configured to preset a similarity coefficient threshold. After calculation, it determines the relationship between the real-time similarity coefficient and the threshold. If the real-time similarity coefficient is greater than or equal to the similarity coefficient threshold, it is determined that the current model parameters are suitable for the current operating scenario, and no parameter calibration process needs to be initiated. If the real-time similarity coefficient is less than the similarity coefficient threshold, it is further determined whether the state of the similarity coefficient being less than the similarity coefficient threshold has occurred continuously for more than a preset number of times. If it has occurred continuously for more than a preset number of times, the parameter calibration process is initiated. If it only occurs once, it is determined to be temporary interference, and calibration is not initiated. The identification and monitoring module is also configured to write the calibrated parameters as update values ​​into the model, while recording update logs and associating update time with the running scenario.

[0010] Furthermore, when the identification and monitoring module is configured to collect insulation and electromagnetic interference data and output abnormal alarm signals, it includes: the identification and monitoring module is also configured to select insulation monitoring points at the high-voltage circuit inlet, outlet and key nodes, and to set up electromagnetic interference collection antennas near the power output end of the high-voltage circuit and the signal interface of the integrated control module. The identification and monitoring module is also configured to set the insulation resistance monitoring frequency and electromagnetic interference acquisition bandwidth, and to acquire insulation resistance values ​​and electromagnetic interference time-domain signals in real time. The identification and monitoring module is also configured to convert the electromagnetic interference time-domain signal into a frequency-domain signal and extract the amplitude at the characteristic frequency. The identification and monitoring module is also configured to preset insulation resistance threshold and electromagnetic interference amplitude threshold. When the insulation resistance value is greater than or equal to the insulation resistance threshold and the electromagnetic interference amplitude is less than or equal to the electromagnetic interference amplitude threshold, the system outputs a normal electrical status signal, indicating the actual insulation resistance value, the actual electromagnetic interference amplitude value and the difference range between the actual insulation resistance value and the corresponding threshold. When the insulation resistance value is greater than or equal to the insulation resistance threshold and the electromagnetic interference amplitude is greater than the electromagnetic interference amplitude threshold, an electromagnetic interference abnormality alarm signal is output, indicating the approximate location of the interference source and the magnitude of the amplitude exceeding the standard. When the insulation resistance value is less than the insulation resistance threshold and the electromagnetic interference amplitude is greater than the electromagnetic interference amplitude threshold, a dual abnormality superposition alarm signal is output, prioritizing the marking of the insulation fault location and simultaneously attaching electromagnetic interference abnormality information; When the insulation resistance value is less than the insulation resistance threshold and the electromagnetic interference amplitude is less than or equal to the electromagnetic interference amplitude threshold, an insulation fault-type abnormal alarm signal is output, highlighting the precise location of the insulation fault, the difference between the actual insulation resistance value and the threshold, and indicating that the electromagnetic interference status is normal.

[0011] Furthermore, when the integrated control module is configured to calculate the power output ratio by combining battery and auxiliary energy parameters, the integrated control module is further configured to establish a power output ratio calculation equation, and the input parameters include operating condition range, task level, battery SOC value, upper limit of battery output power, and auxiliary energy output capability. The integrated control module is also configured to construct the calculation equations as follows: engine output ratio equals base ratio multiplied by operating condition coefficient multiplied by task coefficient, motor output ratio equals the difference between one and the engine output ratio multiplied by SOC coefficient, and auxiliary energy output ratio equals redundancy demand coefficient multiplied by task level coefficient. The integrated control module is also configured to preset operating condition coefficients for different operating condition ranges, task coefficients for different task levels, and SOC coefficients for different SOC values. The integrated control module is also configured to output the real-time output power ratio of the engine, motor, and auxiliary energy to ensure that the total output power matches the load demand and does not exceed the output limit of each energy source.

[0012] Furthermore, when the integrated control module is configured to set the power output ratio adjustment rule, it includes: the integrated control module is also configured to set the time interval for ratio adjustment, and trigger the adjustment according to a fixed time interval or the load change amplitude; The integrated control module is also configured to immediately trigger a proportional adjustment signal when the load demand change exceeds a preset threshold, without waiting for a fixed interval. The integrated control module is also configured to follow the principle of smooth power transition during the adjustment process, and to limit the adjustment range of each energy output ratio in a single instance to no more than the preset maximum value; The integrated control module is also configured to record the operating conditions, tasks, loads, and output ratios of each energy source for each adjustment, forming an adjustment log.

[0013] Furthermore, when the integrated control module is configured to generate charge and discharge thresholds based on temperature and battery cycle count, the integrated control module is further configured to establish a charge and discharge threshold correlation equation, with real-time temperature and battery cumulative cycle count as input parameters, and upper charging threshold and lower discharging threshold as output parameters. The integrated control module is also configured to have a built-in temperature coefficient and cycle number coefficient in the equation. The lower the temperature, the lower the upper limit threshold for charging, and the more cycles, the higher the lower limit threshold for discharging. The integrated control module is also configured to receive power allocation results, and when the motor is in the regenerative power generation state, raise the upper limit charging threshold to the first upper limit charging threshold; when the task requirement is a high load task requirement, relax the lower limit discharging threshold to the first lower limit discharging threshold. The integrated control module is also configured to record the triggering conditions, adjustment range, and adjusted battery operating data for threshold adjustment, and feed them back to the identification and monitoring module for parameter updates.

[0014] Furthermore, when the integrated control module is configured to determine the power supply priority based on load parameters and task level, it includes: the integrated control module is further configured to divide the load parameters into core power load parameters and auxiliary load parameters, wherein the core power load parameters include power demand and start-up sequence, and the auxiliary load parameters include type and running priority; The integrated control module is also configured to establish matching rules: under high task level, the core power load has the highest priority for power supply, and auxiliary loads are sorted according to their relevance to the operation; under low task level, the priority of unnecessary auxiliary loads can be reduced; under medium task level, it can be flexibly adapted. If the operation scenario is close to a high-level task, it will be executed according to the high-level task rules; if it is close to a low-level task, it can be adjusted with reference to the low-level task rules. Among them, high task level corresponds to level four and level five tasks, low task level corresponds to level one and level two tasks, and medium task level corresponds to level three tasks. The integrated control module is also configured to synchronously adjust the priority of auxiliary loads and prioritize cutting off the power supply to low-correlation auxiliary loads when the power output ratio is adjusted, resulting in a change in the total power supply capacity. The integrated control module is also configured to output a power supply priority sequence, which clarifies the power supply order and power outage priority of each load.

[0015] Furthermore, when the identification and monitoring module is configured to output identification results and abnormal alarm signals, the following is included: the identification and monitoring module is also configured to package the identification results, which include real-time operating condition range, task level, and characteristic parameter deviation value, and transmit them to the integrated control module in a fixed format. The identification and monitoring module is also configured to classify abnormal alarm signals according to their severity: Level 1 alarm corresponds to slight electromagnetic interference, Level 2 alarm corresponds to slight deviation in insulation resistance, and Level 3 alarm corresponds to insulation fault, strong electromagnetic interference, and superposition of double abnormalities. The identification and monitoring module is also configured such that first-level and second-level alarms are only transmitted to the integrated control module for parameter adjustment, while third-level alarms are simultaneously transmitted to the integrated control module and the loop switching verification module. The identification and monitoring module is also configured to include the fault occurrence time, location, and parameter deviation data with the alarm signal, facilitating subsequent tracing and processing.

[0016] Furthermore, when the integrated control module is configured to receive the identification result and the alarm signal and output the control signal, it includes: the integrated control module is also configured to, after receiving the identification result, first verify the integrity and validity of the data, and if the data is invalid, it will be fed back to the data acquisition and processing module for re-acquisition; The integrated control module is also configured to reduce the abnormal impact by adjusting the power output ratio or charging / discharging threshold when receiving first-level or second-level alarm signals. Upon receiving a Level 3 alarm signal, the circuit switching trigger signal is immediately output to the circuit switching verification module. The integrated control module is also configured to include a power output ratio command, a charge / discharge threshold command, and a power supply priority command in the control signal, specifying the execution unit, execution parameters, and execution time limit. The integrated control module is also configured to receive feedback results from the loop switching verification module. If the switching is successful, the current control parameters are maintained; if it fails, an emergency control scheme is activated.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The dual-dimensional identification model of working condition and task constructed by the identification and monitoring module, combined with feature parameter mapping, real-time updates and historical data comparison mechanisms, completely solves the problems of single working condition identification dimension and large adaptation deviation in traditional systems, and greatly improves the identification accuracy of special vehicles in complex operating scenarios. At the same time, by scientifically selecting monitoring points, optimizing data acquisition and threshold comparison logic, and cooperating with hierarchical alarm design, it effectively makes up for the blind spots of electrical safety monitoring, realizes the accurate location of insulation and electromagnetic interference faults, and solves the problem of inaccurate safety monitoring.

[0018] 2. The integrated control module dynamically calculates the power output ratio based on multi-source energy parameters, generates charge and discharge thresholds by combining temperature and battery cycle count, and sets power supply priority according to load and task level. This breaks the limitations of traditional fixed allocation strategies, significantly improves power allocation adaptability and energy utilization efficiency, and extends battery life. It also solves the problems of poor power adaptability, low energy efficiency, and unreasonable battery management.

[0019] 3. The path construction module designs primary and backup power supply paths and embeds electromagnetic interference judgment logic. Combined with the intelligent switching, continuity detection, and data feedback functions of the circuit switching verification module, it not only solves the problems of insufficient redundancy and rigid switching conditions in traditional power supply paths, but also realizes rapid and stable switching in case of failure, ensuring power supply continuity. Moreover, each module forms a closed-loop control through the data acquisition and processing module and feedback mechanism, which completely solves the shortcomings of existing technologies that lack effective linkage and cannot be adjusted and optimized in a timely manner, and comprehensively improves the reliability, safety, and operational stability of the power system of special vehicles. Attached Figure Description

[0020] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a functional block diagram of a multi-source hybrid power and intelligent power management system for special vehicles provided in an embodiment of the present invention. Detailed Implementation

[0021] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] Reference Figure 1 In some embodiments of this application, a multi-source hybrid power and intelligent power management system for special vehicles includes: a data acquisition and processing module, an identification and monitoring module, a comprehensive control module, a path construction module, and a loop switching verification module.

[0023] Specifically, the data acquisition and processing module is configured to collect operating status parameters, load parameters, environmental parameters, and electrical status parameters, set the acquisition frequency, establish a buffer unit, and filter and complete invalid data. The identification and monitoring module is configured to establish a dual-dimensional identification model of working conditions and tasks, complete feature parameter mapping, real-time parameter updates and historical data comparison, and simultaneously select monitoring points to collect insulation and electromagnetic interference data. After comparing with preset thresholds, it outputs identification results and abnormal alarm signals. The integrated control module is configured to receive the identification results, calculate the power output ratio by combining battery and auxiliary energy parameters, generate charge and discharge thresholds based on temperature and battery cycle count, determine power supply priority according to load parameters and task level, and output control signals. The path construction module is configured to design primary and backup power supply paths, establish path switching trigger conditions, embed electromagnetic interference judgment logic, and store path connection parameters and drawings. The circuit switching verification module is configured to receive abnormal alarm signals and control signals, perform main and backup circuit switching after verifying the switching conditions, detect the conduction status of the target circuit, record the switching data, and feed the results back to the data acquisition and processing module and the integrated control module.

[0024] Specifically, the data acquisition and processing unit collects operating status parameters (including driving speed 0-120km / h, acceleration -5~5m / s², number of start-stop cycles, and continuous operation time 0-24h), load parameters (including core load power 0-500kW, auxiliary load power 0-50kW, and load fluctuation range ±5%), environmental parameters (including ambient temperature -40℃~60℃, relative humidity 10%~95%, and atmospheric pressure 80~110kPa), and electrical status parameters (including high-voltage circuit voltage 200~800V, current 0-300A, insulation resistance 0~500MΩ, and electromagnetic interference amplitude 0). ~100dBμV), set the acquisition frequency to 10~100Hz (the acquisition frequency for operating status and electrical status parameters is 50~100Hz, and the acquisition frequency for load and environmental parameters is 10~30Hz), and establish a cache unit with a capacity of not less than 8GB; invalid data is processed according to the following rules: invalid data that deviates from the preset rated range of each parameter by ±15% is filtered out. If the deviation value exceeds the upper or lower limit of the rated range, it is directly determined as invalid data; continuous data with a missing ratio of no more than 5% is completed using linear interpolation, and data with a missing ratio of more than 5% is marked as abnormal and a re-acquisition command is triggered.

[0025] Specifically, the path construction model designs the main and backup power supply paths (the main power supply path uses copper core wires with a cross-sectional area of ​​16~50mm², withstand voltage rating ≥1000V, and current carrying capacity ≥300A; the backup power supply path has the same structure as the main power supply path and serves as a redundant backup for each other), establishes path switching trigger conditions (including insulation resistance ≤10MΩ, electromagnetic interference amplitude ≥80dBμV, main circuit power output interruption time ≥50ms, and emergency switching command triggering of the integrated control module), embeds electromagnetic interference judgment logic (sets the interference judgment frequency range to 10kHz~1GHz, and triggers path switching preprocessing when the electromagnetic interference amplitude in this frequency band exceeds the threshold three times consecutively), and stores path connection parameters (including wire length 0.5~5m, connection node voltage drop ≤0.5V, contact resistance ≤5mΩ, insulation rating IP67) and drawings (stored in both PDF and DWG formats, with a drawing update cycle of ≤7 days, a cache capacity of not less than 2GB, and support for offline retrieval and online synchronization).

[0026] Specifically, the circuit switching verification module receives abnormal alarm signals and control signals (signal reception response time ≤ 20ms, signal transmission delay ≤ 5ms), verifies the switching conditions (verification logic execution time ≤ 30ms, switching is deemed valid if any trigger condition is met), and then performs primary / backup circuit switching (switching action completion time ≤ 100ms, voltage fluctuation amplitude during switching ≤ 10% of rated voltage), detects the conduction status of the target circuit (using 1kHz frequency detection, conduction resistance ≤ 100mΩ is considered normal, and consistent results after 3 consecutive detections confirm stable conduction), and records the switching data. The system includes the switching trigger time, trigger reason, switching time, voltage / current values ​​before and after switching, and circuit continuity resistance. The data recording accuracy is: time ±1ms, voltage ±0.1V, current ±0.5A, and resistance ±5mΩ. The data retention period is ≥3 months. The results are fed back to the data acquisition and processing module and the integrated control module within ≤50ms after the switching is completed and the continuity test is qualified. If the switching fails (switching timeout >200ms or continuity test fails), the retry mechanism is immediately triggered (retry times ≤3 times, with an interval of 50ms between each retry). If the retry fails, an emergency alarm signal is output and the faulty circuit is locked.

[0027] The above embodiments, through the dual-dimensional identification model of working condition and task constructed by the identification and monitoring module, combined with feature parameter mapping, real-time updates, and historical data comparison mechanisms, completely solve the problems of single-dimensional working condition identification and large adaptation deviations in traditional systems, significantly improving the identification accuracy in complex operating scenarios of special vehicles. Simultaneously, by scientifically selecting monitoring points, optimizing data acquisition and threshold comparison logic, and coordinating with a tiered alarm design, it effectively compensates for blind spots in electrical safety monitoring, achieving precise location of insulation and electromagnetic interference faults, and solving the problem of inaccurate safety monitoring. The integrated control module dynamically calculates the power output ratio based on multi-source energy parameters, generates charge and discharge thresholds based on temperature and battery cycle count, and sets power supply priorities according to load and task levels, breaking the traditional... The limitations of fixed power allocation strategies are significantly improved by enhancing power allocation adaptability and energy utilization efficiency, while extending battery life and resolving issues such as poor power adaptation, low energy efficiency, and unreasonable battery management. The path construction module designs primary and backup power supply paths and embeds electromagnetic interference judgment logic. Combined with the intelligent switching, continuity detection, and data feedback functions of the circuit switching verification module, it not only solves the problems of insufficient redundancy and rigid switching conditions in traditional power supply paths, but also achieves rapid and stable switching in case of failure, ensuring power supply continuity. Furthermore, each module forms a closed-loop control system through the data acquisition and processing module and feedback mechanism, completely solving the shortcomings of existing technologies that lack effective linkage and cannot be adjusted and optimized in a timely manner, and comprehensively improving the reliability, safety, and operational stability of the special vehicle power system.

[0028] Specifically, when the identification and monitoring module is configured to establish a dual-dimensional identification model of working conditions and tasks, it includes: the identification and monitoring module is also configured to select start-stop frequency, load fluctuation amplitude, and driving speed as working condition characteristic parameters, and select job type, job duration, and load demand as task characteristic parameters; The identification and monitoring module is also configured to divide operating condition ranges, which are divided into stable operating conditions, fluctuating operating conditions, and impact operating conditions according to the combination of start-stop frequency and load fluctuation amplitude, and into low-speed operating conditions, medium-speed operating conditions, and high-speed operating conditions according to driving speed. The identification and monitoring module is also configured to classify tasks into five levels based on the combination of job complexity and load requirements. The higher the level, the higher the job complexity and the greater the load requirements. The identification and monitoring module is also configured to establish a mapping table between working condition characteristic parameters and task levels, and to clarify the adaptation characteristic thresholds for each task level under different working condition ranges.

[0029] Specifically, when the identification and monitoring module establishes a dual-dimensional identification model for operating conditions and tasks, it selects start-stop frequency, load fluctuation amplitude, and driving speed as operating condition characteristic parameters, and selects operation type, operation duration, and load demand as task characteristic parameters. Among them, the start-stop frequency is divided into intervals of 0~2 times / minute, 2~5 times / minute, and >5 times / minute; the load fluctuation amplitude is divided into intervals of ≤±5%, ±5%~±15%, and >±15%; and the driving speed is divided into intervals of ≤20km / h, 20~60km / h, and >60km / h. Based on this, the operating conditions are divided into stable operating conditions (start-stop frequency ≤2 times / minute and load fluctuation amplitude ≤±5%), fluctuating operating conditions (start-stop frequency 2~5 times / minute and load fluctuation amplitude ±5%~±15%), and impact operating conditions (start-stop frequency >5 times / minute and load fluctuation amplitude >±15%), and correspondingly divided into low-speed operating conditions, medium-speed operating conditions, and high-speed operating conditions. Based on the combination of operational complexity (simple / relatively simple / medium / relatively complex / complex) and load requirements (≤50kW / 50~100kW / 100~200kW / 200~300kW / ≥300kW), tasks are divided into five levels, from Level 1 to Level 5. The higher the level, the higher the operational complexity and the greater the load requirements. Level 1 tasks correspond to simple operations and load requirements of ≤50kW, while Level 5 tasks correspond to complex operations and load requirements of ≥300kW. On this basis, a mapping table between operating condition characteristic parameters and task levels is established, clarifying the adaptation characteristic thresholds for each task level under different operating condition ranges. For example, under stable-low speed conditions, Level 1 tasks are adapted to a start-stop frequency of ≤1 time / minute and a load fluctuation range of ≤±3%, while under impact-high speed conditions, Level 5 tasks are adapted to a start-stop frequency of ≥6 times / minute and a load fluctuation range of ≥±18%, etc., to ensure that the model can accurately match different operating scenarios and operational requirements of special vehicles.

[0030] In the above embodiments, the dual-dimensional recognition model accurately selects the core feature parameters of working conditions and tasks, refines the working condition range and task level division by combining specific numerical standards, and establishes a clear mapping relationship table between feature parameters and task levels. This completely solves the problems of low accuracy and poor adaptability of traditional single-dimensional recognition, and can accurately match the different operating conditions and task requirements of special vehicles. It provides reliable basic data support for subsequent comprehensive control and safety monitoring, and greatly improves the adaptability of the entire power and energy management system to complex operating scenarios.

[0031] Specifically, when the identification and monitoring module is configured to complete real-time parameter updates and historical data comparison, it includes: the identification and monitoring module is also configured to set a dual-trigger update mechanism, first determining whether the vehicle is in operation; if in operation, triggering model parameter updates at mileage intervals; if in non-operation, triggering updates at time intervals, with the update frequency in operation being higher than in non-operation. The identification and monitoring module is also configured to call up the working condition and task matching data in the historical operation database, first determine whether the operation scenario corresponding to the retrieved historical data is consistent with the current scenario; if consistent, directly calculate the similarity coefficient between the real-time feature parameters and the historical data; if inconsistent, filter out the historical data with a scenario matching degree higher than the preset matching degree threshold, and then calculate the similarity coefficient. The identification and monitoring module is also configured to preset a similarity coefficient threshold. After calculation, it judges the relationship between the real-time similarity coefficient and the threshold. If the real-time similarity coefficient is greater than or equal to the similarity coefficient threshold, it is determined that the current model parameters are suitable for the current operating scenario, and no parameter calibration process needs to be started. If the real-time similarity coefficient is less than the similarity coefficient threshold, it is further judged whether the state of the similarity coefficient being less than the similarity coefficient threshold has occurred continuously for more than a preset number of times. If it has occurred continuously for more than a preset number of times, the parameter calibration process is started. If it only occurs once, it is determined to be a temporary interference, and calibration is not started. The identification and monitoring module is also configured to write the calibrated parameters as update values ​​into the model, while recording update logs and associating update time with the running scenario.

[0032] Specifically, when the identification and monitoring module completes real-time parameter updates and historical data comparison, its core is to ensure the dynamic adaptation of model parameters to vehicle operating scenarios through a refined mechanism. It first sets up a dual-trigger update mechanism, prioritizing the determination of whether the vehicle is in operation. In operation mode, model parameters are updated every 5km of driving distance, while in non-operation mode, updates are triggered every 30 minutes. The update frequency in operation mode (every 5km / time) is significantly higher than in non-operation mode (every 30 minutes / time), ensuring that parameters closely follow scenario changes during operation. Then, it calls the operating condition and task matching data from the historical operating database. It first verifies whether the operating scenario corresponding to the retrieved historical data is consistent with the current scenario. If consistent, it directly calculates the similarity coefficient between real-time feature parameters and historical data; if inconsistent, it first filters out scenarios with a higher matching degree. The similarity coefficient is calculated again using historical data at a preset threshold of 80%. A similarity coefficient threshold of 0.8 is also preset. After calculation, the real-time coefficient is compared with this threshold. If the real-time similarity coefficient is ≥0.8, the current model parameters are considered suitable for the current operating scenario, and calibration is not required. If the real-time coefficient is <0.8, it is further determined whether this state has occurred more than a preset number of times consecutively. If it has occurred more than three times consecutively, the parameter calibration process is initiated. If it only occurs once, it is considered a temporary disturbance, and calibration is not initiated to avoid invalid operations. After calibration, the module writes the calibrated parameters as updated values ​​into the working condition-task dual-dimensional recognition model, and records detailed update logs, clearly specifying the associated update time, current operating scenario (including working condition range and task level), and key parameter changes, providing complete data support for subsequent parameter tracing and model optimization.

[0033] The above embodiments demonstrate that the real-time parameter update and historical data comparison mechanism adapts to the differences between working and non-working states through a dual-trigger update strategy. Combined with scenario matching and similarity coefficient threshold judgment, along with continuous anomaly trigger calibration and log traceability design, it solves the problems of rigid parameter updates, low comparison accuracy, and strong calibration blindness in traditional methods. This achieves dynamic and accurate adaptation of model parameters to the operating scenario, effectively avoids the impact of temporary interference on calibration, ensures the continuous reliability of the working condition-task identification model, and provides accurate and stable parameter support for the subsequent intelligent control of the system.

[0034] Specifically, when the identification and monitoring module is configured to collect insulation and electromagnetic interference data and output abnormal alarm signals, it includes: the identification and monitoring module is also configured to select insulation monitoring points at the high-voltage circuit inlet, outlet and key nodes, and to set up electromagnetic interference collection antennas near the power output end of the high-voltage circuit and the signal interface of the integrated control module. The identification and monitoring module is also configured to set the insulation resistance monitoring frequency and electromagnetic interference acquisition bandwidth, and to acquire insulation resistance values ​​and electromagnetic interference time-domain signals in real time. The identification and monitoring module is also configured to convert electromagnetic interference time-domain signals into frequency-domain signals and extract the amplitude at characteristic frequencies; The identification and monitoring module is also configured to preset insulation resistance threshold and electromagnetic interference amplitude threshold. When the insulation resistance value is greater than or equal to the insulation resistance threshold and the electromagnetic interference amplitude is less than or equal to the electromagnetic interference amplitude threshold, the system outputs a normal electrical status signal, indicating the actual insulation resistance value, the actual electromagnetic interference amplitude value and the range of difference between the actual insulation resistance value and the corresponding threshold. When the insulation resistance value is greater than or equal to the insulation resistance threshold and the electromagnetic interference amplitude is greater than the electromagnetic interference amplitude threshold, an electromagnetic interference abnormality alarm signal is output, indicating the approximate location of the interference source and the magnitude of the amplitude exceeding the standard. When the insulation resistance value is less than the insulation resistance threshold and the electromagnetic interference amplitude is greater than the electromagnetic interference amplitude threshold, a dual abnormality superposition alarm signal is output, prioritizing the marking of the insulation fault location and simultaneously attaching electromagnetic interference abnormality information; When the insulation resistance value is less than the insulation resistance threshold and the electromagnetic interference amplitude is less than or equal to the electromagnetic interference amplitude threshold, an insulation fault-type abnormal alarm signal is output, highlighting the precise location of the insulation fault, the difference between the actual insulation resistance value and the threshold, and indicating that the electromagnetic interference status is normal.

[0035] Specifically, when the identification and monitoring module collects insulation and electromagnetic interference data and outputs abnormal alarm signals, insulation monitoring points are selected at the high-voltage circuit's incoming and outgoing ends, as well as key nodes (such as contactor and fuse connection points). Electromagnetic interference acquisition antennas are set near the power output end of the high-voltage circuit and the signal interface of the integrated control module (5-10cm from the interface). Simultaneously, the insulation resistance monitoring frequency is set to 1 time / second, and the electromagnetic interference acquisition bandwidth is set to 10kHz-1GHz, thereby collecting insulation resistance values ​​and electromagnetic interference time-domain signals in real time. After acquisition, the electromagnetic interference time-domain signal is converted to a frequency-domain signal using Fourier transform, and the amplitude at characteristic frequencies such as 30MHz, 100MHz, and 500MHz is extracted. The insulation resistance threshold is preset to 10MΩ, and the electromagnetic interference amplitude threshold is preset to 80dBμV. Corresponding signals are output according to four operating conditions: when the insulation resistance value is ≥10MΩ and the electromagnetic interference amplitude is ≤80dBμV... When the insulation resistance is ≥10MΩ and the electromagnetic interference amplitude is >80dBμV, an electromagnetic interference-related alarm signal is output, indicating the actual value of the insulation resistance, the actual value of the electromagnetic interference amplitude, and the range of difference between the actual value and the corresponding threshold. When the insulation resistance is ≥10MΩ and the electromagnetic interference amplitude is >80dBμV, an electromagnetic interference-related alarm signal is output, indicating the approximate location of the interference source (e.g., power output area, signal interface area) and the amplitude exceeding the standard. When the insulation resistance is <10MΩ and the electromagnetic interference amplitude is >80dBμV, a dual-abnormal superimposed alarm signal is output, prioritizing the precise location of the insulation fault (e.g., the A-phase node at the incoming line), and simultaneously attaching electromagnetic interference abnormal information. When the insulation resistance is <10MΩ and the electromagnetic interference amplitude is ≤80dBμV, an insulation fault-related alarm signal is output, highlighting the precise location of the insulation fault, the difference between the actual insulation resistance and the 10MΩ threshold, and indicating that the electromagnetic interference status is normal, ensuring accurate identification, classification alarm, and information traceability of electrical safety anomalies.

[0036] The above embodiments, by scientifically selecting key points in the high-voltage circuit to set up monitoring points and electromagnetic interference acquisition antennas, rationally setting the monitoring frequency and acquisition bandwidth, combining time-domain to frequency-domain signal conversion and feature amplitude extraction technology, and coupled with a graded threshold judgment and classification alarm mechanism, accurately output signals of different electrical states and mark fault locations, actual parameters and exceedance information. This effectively solves the problems of blind spots, low accuracy of interference identification, unclear fault type distinction and ambiguous location in traditional electrical safety monitoring, and achieves comprehensive coverage, accurate identification and rapid source tracing of insulation and electromagnetic interference anomalies. It provides reliable data support for system emergency switching and fault handling, and significantly improves the operational safety and fault response efficiency of the electrical system of special vehicles.

[0037] Specifically, when the integrated control module is configured to calculate the power output ratio by combining battery and auxiliary energy parameters, the integrated control module is also configured to establish a power output ratio calculation equation, and the input parameters include operating condition range, task level, battery SOC value, battery output power limit, and auxiliary energy output capability. The integrated control module is also configured to calculate the equations as follows: engine output ratio equals base ratio multiplied by operating condition coefficient multiplied by task coefficient; motor output ratio equals the difference between one and the engine output ratio multiplied by SOC coefficient; and auxiliary energy output ratio equals redundancy demand coefficient multiplied by task level coefficient. The integrated control module is also configured to preset operating condition coefficients for different operating condition ranges, task coefficients for different task levels, and SOC coefficients for different SOC values. The integrated control module is also configured to output the real-time output power ratio of the engine, motor, and auxiliary energy to ensure that the total output power matches the load demand and does not exceed the output limit of each energy source.

[0038] Specifically, when the integrated control module calculates the power output ratio based on battery and auxiliary energy parameters, it establishes a specific power output ratio calculation equation. The input parameters include the operating range, task level, battery SOC value (0%~100%), battery output power limit (0~300kW), and auxiliary energy output capacity (0~100kW). This calculation equation is constructed according to the following logic: the engine output ratio equals the preset benchmark ratio (0.5) multiplied by the operating condition coefficient (0.8 for stable operating conditions, 1.0 for fluctuating operating conditions, and 1.2 for impact operating conditions) multiplied by the task coefficient (0.6 for Level 1 task, 0.7 for Level 2 task, 0.8 for Level 3 task, 0.9 for Level 4 task, and 1.0 for Level 5 task); the motor output ratio equals (1 - engine output ratio) multiplied by the SOC coefficient (SOC≥80%). The coefficients are 1.0 for 50%~80%, 0.9 for 30%~50%, 0.7 for <30%, and 0.5 for <30%). The auxiliary energy output ratio is equal to the redundancy demand coefficient (0.1~0.3) multiplied by the task level coefficient (consistent with the task coefficient). At the same time, the module presets the operating condition coefficients corresponding to different operating condition ranges, the task coefficients corresponding to different task levels, and the SOC coefficients corresponding to different SOC value ranges. By substituting the real-time collected input parameters into the equation for dynamic calculation, the module finally outputs the real-time output power ratio of the engine, motor, and auxiliary energy, ensuring that the total output power accurately matches the current load demand, and that the output power of each energy source does not exceed its own output limit (the battery does not exceed the output power limit, and the auxiliary energy does not exceed its own output capacity), thus realizing the coordinated and optimized allocation of multi-source power.

[0039] The above embodiments establish a power output ratio calculation equation that integrates multi-dimensional parameters such as operating conditions, tasks, batteries, and auxiliary energy. Combined with differentiated preset coefficients and output upper limit constraints, the real-time power ratio of the engine, motor, and auxiliary energy is dynamically output. This solves the problems of poor adaptability, low energy efficiency, and output overload risk caused by the fixed and rigid traditional power distribution strategy and insufficient correlation of multi-source parameters. It achieves precise coordinated distribution of multi-source power, ensures accurate matching between total output power and load demand, and avoids exceeding the output limits of each energy source. This significantly improves the energy utilization efficiency, operating condition adaptability, and operational stability of the special vehicle power system.

[0040] Specifically, when the integrated control module is configured to set the power output ratio adjustment rules, it includes: the integrated control module is also configured to set the time interval for ratio adjustment, and trigger the adjustment according to a fixed time interval or the load change amplitude; The integrated control module is also configured to immediately trigger a proportional adjustment signal when the change in load demand exceeds a preset threshold, without waiting for a fixed interval. The integrated control module is also configured to follow the principle of smooth power transition during the adjustment process, limiting the adjustment range of each energy output ratio in a single instance to no more than the preset maximum value; The integrated control module is also configured to record the operating conditions, tasks, loads, and output ratios of each energy source for each adjustment, forming an adjustment log.

[0041] Specifically, when setting the power output ratio adjustment rules in the integrated control module, a fixed time interval of 100ms is set for the ratio adjustment. It also supports adjustments triggered by load changes, with a preset load demand change threshold of ±10%. When the load demand change exceeds this threshold, a ratio adjustment signal is immediately triggered without waiting for the fixed time interval, ensuring that power distribution can quickly respond to sudden load changes. During the adjustment process, the principle of smooth power transition is strictly followed, limiting the adjustment range of the engine, motor, and auxiliary energy output ratio to no more than a preset maximum of 5% for each adjustment. This avoids power output fluctuations or electrical system shocks caused by sudden ratio changes. Simultaneously, detailed data such as the operating condition range, task level, real-time load parameters, and the output ratios of the engine, motor, and auxiliary energy before, after, and the adjustment range for each adjustment are recorded, forming a complete adjustment log. This provides a traceable data analysis foundation for subsequent adjustment rule optimization and power distribution strategy iteration.

[0042] In the above embodiments, the power output ratio adjustment rule solves the problem of lag in traditional adjustment response by setting a fixed time interval and a dual trigger mechanism of load change amplitude, combined with an instant adjustment design for load mutations, ensuring that power distribution can quickly adapt to dynamic load changes. At the same time, by limiting the power smooth transition principle of single adjustment amplitude, it avoids power fluctuations and electrical system shocks caused by ratio mutations, ensuring operational stability. The complete adjustment log records provide traceable data support for strategy optimization, effectively making up for the shortcomings of traditional rules that lack adjustment traceability and iteration basis, and comprehensively improving the responsiveness, operational stability and strategy optimizability of multi-source power distribution.

[0043] Specifically, when the integrated control module is configured to generate charge and discharge thresholds based on temperature and battery cycle count, the integrated control module is also configured to establish a charge and discharge threshold correlation equation, with real-time temperature and battery cumulative cycle count as input parameters, and upper charging threshold and lower discharging threshold as output parameters. The integrated control module is also configured with built-in temperature coefficient and cycle number coefficient in the equation. The lower the temperature, the lower the upper limit threshold for charging, and the more cycles, the higher the lower limit threshold for discharging. The integrated control module is also configured to receive power allocation results, and when the motor is in the regenerative braking state, raise the upper limit charging threshold to the first upper limit charging threshold; when the task demand is a high load task demand, relax the lower limit discharging threshold to the first lower limit discharging threshold. The integrated control module is also configured to record the triggering conditions, adjustment range, and adjusted battery operating data for threshold adjustment, and feed them back to the identification and monitoring module for parameter updates.

[0044] Specifically, when the integrated control module calculates the power output ratio based on battery and auxiliary energy parameters, it establishes a specific power output ratio calculation equation. The input parameters include the operating range, task level, battery SOC value (0%~100%), battery output power limit (0~300kW), and auxiliary energy output capacity (0~100kW). This calculation equation is constructed according to the following logic: the engine output ratio equals the preset benchmark ratio (0.5) multiplied by the operating condition coefficient (0.8 for stable operating conditions, 1.0 for fluctuating operating conditions, and 1.2 for impact operating conditions) multiplied by the task coefficient (0.6 for Level 1 task, 0.7 for Level 2 task, 0.8 for Level 3 task, 0.9 for Level 4 task, and 1.0 for Level 5 task); the motor output ratio equals (1 - engine output ratio) multiplied by the SOC coefficient (1.0 for SOC ≥ 80%, 0.9 for 50%~80%, 0.7 for 30%~50%, and 0.5 for < 30%); the auxiliary energy output ratio equals... The redundancy requirement factor (0.1~0.3) is multiplied by the task factor (consistent with the task factor) and then multiplied by (1 - engine output ratio - motor output ratio) to ensure that the total output ratio of the engine, motor, and auxiliary energy is ≤100%. At the same time, the module presets the operating condition factor corresponding to different operating condition ranges, the task factor corresponding to different task levels, and the SOC factor corresponding to different SOC value ranges. By substituting the real-time collected input parameters into the equation for dynamic calculation, the module finally outputs the real-time output power ratio of the engine, motor, and auxiliary energy, ensuring that the total output power accurately matches the current load demand, and that the output power of each energy source does not exceed its own output limit (battery does not exceed the output power limit, and auxiliary energy does not exceed its own output capacity). If the total output power still cannot meet the load demand after calculation, the low-correlation auxiliary loads are cut off according to the power supply priority sequence until the total output power matches the remaining load demand, thereby achieving the coordinated optimization allocation of multi-source power.

[0045] In the above embodiments, the integrated control module establishes a correlation equation between the real-time battery temperature and the cumulative number of cycles for the charge-discharge threshold. It dynamically adapts the threshold using temperature and cycle number coefficients, flexibly adjusting the threshold based on the motor's regenerative braking status and high-load task requirements. Furthermore, it supports model parameter iteration through data recording and feedback mechanisms. This solves the problems of high battery damage risk, insufficient energy utilization, and poor task adaptability caused by traditional fixed charge-discharge thresholds that do not adequately consider battery environmental conditions, aging levels, and special operating conditions. It achieves precise matching of charge-discharge thresholds with battery status and operating scenarios, effectively avoiding potential damage such as low-temperature overcharging and over-discharging of aging batteries. This improves the utilization rate of regenerative braking energy and the stability of power supply under high-load tasks. Simultaneously, it provides data support for parameter updates in the identification and monitoring module, extending battery life and enhancing the operational reliability and scenario adaptability of the entire power management system.

[0046] Specifically, when the integrated control module is configured to determine power supply priority based on load parameters and task level, it includes: the integrated control module is also configured to divide the load parameters into core power load parameters and auxiliary load parameters, the core power load parameters including power demand and start-up sequence, and the auxiliary load parameters including type and operation priority; The integrated control module is also configured to establish matching rules: under high task level, the core power load has the highest priority for power supply, and auxiliary loads are sorted according to their relevance to the operation; under low task level, the priority of unnecessary auxiliary loads can be reduced; under medium task level, it can be flexibly adapted. If the operation scenario is close to a high task level, it will be executed according to the high task level rules; if it is close to a low task level, it can be adjusted with reference to the low task level rules. Among them, high task level corresponds to level four and level five tasks, low task level corresponds to level one and level two tasks, and medium task level corresponds to level three tasks. The integrated control module is also configured to adjust the priority of auxiliary loads synchronously when the adjustment of the power output ratio causes a change in the total power supply capacity, and to prioritize cutting off the power supply to low-relevance auxiliary loads. The integrated control module is also configured to output a power supply priority sequence, which clarifies the power supply order and power outage priority of each load.

[0047] Specifically, when the integrated control module determines the power supply priority based on load parameters and task level, it divides the load parameters into core power load parameters and auxiliary load parameters. Core power load parameters include load power requirements (50~300kW) and start-up sequence (start-up interval ≥100ms). Auxiliary load parameters include load type (e.g., lighting load, communication load, heat dissipation load, etc.) and preset operating priority (levels 1~5, with level 1 being the highest). Simultaneously, clear matching rules are established: under high task levels (corresponding to levels four and five), the core power load has the highest power supply priority, ensuring uninterrupted core power supply for the operation. Auxiliary loads are sorted according to their relevance to the current operation (loads directly related to the operation, such as equipment control loads > indirectly related loads, such as auxiliary heat dissipation loads > unrelated loads, such as redundant lighting loads). Under low task levels (corresponding to levels one and two), the power supply priority of unnecessary auxiliary loads (such as redundant communication modules and backup lighting) can be reduced, allowing for priority power cut-off during power shortages. A flexible adaptation mechanism is adopted for medium task levels (corresponding to level three). If the load demand and operating intensity of the work scenario are close to those of a high-level task (e.g., load fluctuation ≥ ±10%, work complexity reaches a relatively complex level), the power supply priority allocation will be executed according to the high-level task rules. If the scenario is close to that of a low-level task (e.g., load demand ≤ 100kW, work complexity is simple / relatively simple), the auxiliary load priority can be adjusted with reference to the low-level task rules. When the adjustment of the power output ratio causes a change in the total power supply capacity (e.g., a decrease in total power supply capacity ≥ 15%), the module will synchronously and dynamically adjust the auxiliary load priority, prioritizing the disconnection of the auxiliary load with the lowest work relevance to avoid affecting the operation of the core power load and critical auxiliary load. Finally, a clear power supply priority sequence will be output, detailing the power supply order of each load (core power load > work-directly related auxiliary load > work-indirectly related auxiliary load > non-related auxiliary load) and the power outage priority (non-related auxiliary load > work-indirectly related auxiliary load > work-directly related auxiliary load, core power load is not included in the active power outage range), ensuring that power supply resources are accurately matched with task requirements and load importance.

[0048] The above embodiments demonstrate that the power supply priority determination mechanism, by clearly defining the parameter categories of core power loads and auxiliary loads, establishes differentiated matching rules based on high, medium, and low task levels. Combined with dynamic priority adjustment when power supply capacity changes and clear power supply / power outage sequence output, it solves the problems of fixed and rigid power supply priorities, insufficient core load protection, and unreasonable allocation of auxiliary load resources in traditional systems. This achieves precise matching of power supply resources with task requirements and load importance, ensuring stable power supply to core power loads under high task levels, while flexibly optimizing the power supply allocation of auxiliary loads under low / medium task levels. When power supply capacity fluctuates, it prioritizes cutting off low-relevance auxiliary loads to ensure the continuous operation of critical functions, significantly improving the resource utilization efficiency, core operation continuity, and adaptability to complex scenarios of the special vehicle power supply system.

[0049] Specifically, when the identification and monitoring module is configured to output identification results and abnormal alarm signals, the identification and monitoring module is also configured to package the identification results, including real-time operating condition range, task level, and characteristic parameter deviation value, and transmit them to the integrated control module in a fixed format. The identification and monitoring module is also configured to classify abnormal alarm signals according to their severity: Level 1 alarm corresponds to minor electromagnetic interference, Level 2 alarm corresponds to slight deviation in insulation resistance, and Level 3 alarm corresponds to insulation fault, strong electromagnetic interference, and superposition of dual abnormalities. The identification and monitoring module is also configured such that first- and second-level alarms are only transmitted to the integrated control module for parameter adjustment, while third-level alarms are transmitted synchronously to both the integrated control module and the loop switching verification module. The identification and monitoring module is also configured to include alarm signals with fault occurrence time, location, and parameter deviation data, facilitating subsequent tracing and processing.

[0050] Specifically, when the identification and monitoring module outputs identification results and abnormal alarm signals, it packages the identification results into a fixed data format and transmits them to the integrated control module. This identification result includes the vehicle's real-time operating condition range, the current task level, and deviations of various characteristic parameters (such as start-stop frequency, load fluctuation amplitude, insulation resistance value, etc.), ensuring that the integrated control module can quickly obtain accurate basic data support. Simultaneously, abnormal alarm signals are divided into three levels according to severity: Level 1 alarms correspond to minor electromagnetic interference (amplitude exceeding the threshold but ≤10dBμV), Level 2 alarms correspond to slight deviations in insulation resistance (actual value ≥5MΩ and <10MΩ), and Level 3 alarms correspond to insulation faults (insulation resistance value <5MΩ) and strong electromagnetic interference (amplitude exceeding the threshold). The system handles cases where the threshold value is greater than 10 dBμV and cases involving the superposition of insulation and electromagnetic interference anomalies. It clearly defines the transmission paths for each alarm level: Level 1 and Level 2 alarms are transmitted only to the integrated control module for dynamic adjustment of parameters such as power output ratio and charge / discharge threshold; Level 3 alarms are transmitted simultaneously to both the integrated control module and the loop switching verification module, ensuring that core faults can simultaneously trigger control optimization and safe switching preparation. All alarm signals are accompanied by complete traceability information, including the precise time of the fault occurrence (accurate to milliseconds), the fault location (such as specific insulation monitoring nodes or electromagnetic interference acquisition areas), and parameter deviation data (including actual values, thresholds, and differences), providing comprehensive and traceable data for subsequent fault investigation, cause analysis, and system optimization.

[0051] The above embodiments, by packaging and transmitting identification results containing real-time operating condition ranges, task levels, and characteristic parameter deviation values ​​in a fixed format, provide accurate and unified decision-making basis for the comprehensive control module. Simultaneously, abnormal alarm signals are graded according to severity and differentiated transmission paths are clearly defined. Level 1 and 2 alarms provide directional support for dynamic parameter adjustments, while Level 3 alarms synchronously trigger control optimization and safety switching preparation. Furthermore, all alarm signals are accompanied by fault time, location, and parameter deviation data. This effectively solves the problems of chaotic transmission formats of traditional identification results, inaccurate responses due to the lack of alarm grading, and difficulties in fault tracing. It achieves efficient adaptation of identification data, accurate grading of abnormal situations, and traceable fault handling, significantly improving the timeliness of decision-making, the targeted nature of fault handling, and operational safety of the special vehicle power management system, while reducing subsequent maintenance costs.

[0052] Specifically, when the integrated control module is configured to receive identification results and alarm signals and output control signals, it includes: after receiving identification results, the integrated control module is also configured to first verify the integrity and validity of the data, and if the data is invalid, it will be fed back to the data acquisition and processing module for re-acquisition. The integrated control module is also configured to reduce the impact of abnormalities by adjusting the power output ratio or charging / discharging threshold when receiving first-level or second-level alarm signals. Upon receiving a Level 3 alarm signal, the circuit switching trigger signal is immediately output to the circuit switching verification module. The integrated control module is also configured to include power output ratio instructions, charge / discharge threshold instructions, and power supply priority instructions in the control signals, clearly defining the execution unit, execution parameters, and execution time limit. The integrated control module is also configured to receive feedback results from the loop switching verification module. If the switching is successful, the current control parameters are maintained; if it fails, an emergency control plan is activated.

[0053] Specifically, when the integrated control module receives the identification results and alarm signals and outputs control signals, it first verifies the data integrity (including whether core fields such as real-time operating range, task level, and characteristic parameter deviation values ​​are complete) and validity (whether the parameters are within the preset reasonable range and whether the format conforms to fixed standards) after receiving the identification results. If the data is determined to be invalid (such as missing key parameters, parameters exceeding reasonable thresholds, or incorrect format), it immediately feeds back to the data acquisition and processing module to trigger a re-acquisition process. When receiving first-level and second-level alarm signals, it weakens the abnormal impact and avoids the abnormality from escalating by dynamically adjusting the power output ratio (such as optimizing the power ratio of the engine, motor, and auxiliary energy) or charging and discharging thresholds (such as fine-tuning the upper limit of charging and the lower limit of discharging). When receiving a third-level alarm signal, it immediately outputs a loop switching trigger. The signal-to-loop switching verification module outputs control signals that explicitly include three core commands: power output ratio command, charge / discharge threshold command, and power supply priority command. Each command clearly indicates the execution unit (e.g., engine control unit, battery management unit, load control unit), specific execution parameters (e.g., power output ratio value, charge / discharge threshold range, power supply priority sequence), and execution time limit (e.g., immediate execution, execution completed within 100ms). In addition, the module continuously receives switching results from the loop switching verification module. If the switching is successful, the current control parameters are maintained in stable operation. If the switching fails, an emergency control plan is immediately activated (e.g., locking the core power load supply, reducing unnecessary load power, and activating backup energy output) to ensure that the system can still guarantee the normal operation of core functions under extreme conditions.

[0054] In the above embodiments, the integrated control module, after receiving the identification results, first verifies the integrity and validity of the data and triggers the re-collection of invalid data to ensure the accuracy and reliability of the control decision-making basis. Different processing is adopted for alarm signals of different levels. Level 1 and Level 2 alarms are weakened by adjusting the power output ratio or charging and discharging thresholds to reduce the abnormal impact. Level 3 alarms immediately trigger loop switching and synchronously output control instructions containing clear execution units, parameters and time limits. At the same time, the control parameters are dynamically maintained or emergency plans are activated based on the feedback results of loop switching. This effectively solves the problems of insufficient data reliability, undifferentiated alarm response, ambiguous control instructions and lack of fault emergency closed loop in traditional control systems. It realizes accurate hierarchical handling of abnormal situations, efficient implementation of control instructions and full-process closed loop of fault handling, significantly improving the decision-making accuracy, response timeliness and operational fault tolerance of the special vehicle power management system, and ensuring the continuous stability of core operating functions.

[0055] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0056] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0057] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0058] These computer program instructions can also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0059] 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 it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A multi-source hybrid power and intelligent power management system for special vehicles, characterized in that, include: The data acquisition and processing module is configured to collect operating status parameters, load parameters, environmental parameters, and electrical status parameters, set the acquisition frequency, establish a buffer unit, and filter and complete invalid data. The identification and monitoring module is configured to establish a dual-dimensional identification model of working conditions and tasks, complete feature parameter mapping, real-time parameter updates and historical data comparison, and simultaneously select monitoring points to collect insulation and electromagnetic interference data. After comparing with preset thresholds, it outputs identification results and abnormal alarm signals. The integrated control module is configured to receive the identification results, calculate the power output ratio by combining battery and auxiliary energy parameters, generate charge and discharge thresholds based on temperature and battery cycle count, determine power supply priority according to load parameters and task level, and output control signals. The path construction module is configured to design primary and backup power supply paths, establish path switching trigger conditions, embed electromagnetic interference judgment logic, and store path connection parameters and drawings. The circuit switching verification module is configured to receive abnormal alarm signals and control signals, perform main and backup circuit switching after verifying the switching conditions, detect the conduction status of the target circuit, record the switching data, and feed the results back to the data acquisition and processing module and the integrated control module.

2. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 1, characterized in that, When the identification and monitoring module is configured to establish a dual-dimensional identification model of working conditions and tasks, it includes: The identification and monitoring module is also configured to select start-stop frequency, load fluctuation amplitude, and driving speed as operating condition characteristic parameters, and select job type, job duration, and load demand as task characteristic parameters. The identification and monitoring module is also configured to divide the operating condition range, which is divided into stable operating condition, fluctuating operating condition, and impact operating condition according to the combination of start and stop frequency and load fluctuation amplitude, and into low speed operating condition, medium speed operating condition, and high speed operating condition according to driving speed. The identification and monitoring module is also configured to classify tasks into five levels based on the combination of job complexity and load requirements. The higher the level, the higher the job complexity and the greater the load requirements. The identification and monitoring module is also configured to establish a mapping table between working condition characteristic parameters and task levels, and to clarify the adaptation characteristic thresholds for each task level under different working condition ranges.

3. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 2, characterized in that, The identification and monitoring module is configured to perform real-time parameter updates and historical data comparisons, including: The identification and monitoring module is also configured to set a dual-trigger update mechanism, first determining whether the vehicle is in operation; if in operation, the model parameters are updated according to the mileage interval; if in non-operation, the update is triggered according to the time interval, and the update frequency in operation is higher than that in non-operation. The identification and monitoring module is also configured to call the working condition and task matching data in the historical operation database, first determine whether the operation scenario corresponding to the retrieved historical data is consistent with the current scenario; if consistent, directly calculate the similarity coefficient between the real-time feature parameters and the historical data; if inconsistent, filter out the historical data with a scenario matching degree higher than the preset matching degree threshold, and then calculate the similarity coefficient. The identification and monitoring module is also configured to preset a similarity coefficient threshold. After calculation, it determines the relationship between the real-time similarity coefficient and the threshold. If the real-time similarity coefficient is greater than or equal to the similarity coefficient threshold, it is determined that the current model parameters are suitable for the current operating scenario, and no parameter calibration process needs to be initiated. If the real-time similarity coefficient is less than the similarity coefficient threshold, it is further determined whether the state of the similarity coefficient being less than the similarity coefficient threshold has occurred continuously for more than a preset number of times. If it has occurred continuously for more than a preset number of times, the parameter calibration process is initiated. If it only occurs once, it is determined to be temporary interference, and calibration is not initiated. The identification and monitoring module is also configured to write the calibrated parameters as update values ​​into the model, while recording update logs and associating update time with the running scenario.

4. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 3, characterized in that, When the identification and monitoring module is configured to collect insulation and electromagnetic interference data and output abnormal alarm signals, it includes: The identification and monitoring module is also configured to select insulation monitoring points at the high-voltage circuit inlet, outlet and key nodes, and to set up electromagnetic interference acquisition antennas near the power output end of the high-voltage circuit and the signal interface of the integrated control module. The identification and monitoring module is also configured to set the insulation resistance monitoring frequency and electromagnetic interference acquisition bandwidth, and to acquire insulation resistance values ​​and electromagnetic interference time-domain signals in real time. The identification and monitoring module is also configured to convert the electromagnetic interference time-domain signal into a frequency-domain signal and extract the amplitude at the characteristic frequency. The identification and monitoring module is also configured to preset insulation resistance threshold and electromagnetic interference amplitude threshold. When the insulation resistance value is greater than or equal to the insulation resistance threshold and the electromagnetic interference amplitude is less than or equal to the electromagnetic interference amplitude threshold, the system outputs a normal electrical status signal, indicating the actual insulation resistance value, the actual electromagnetic interference amplitude value and the difference range between the actual insulation resistance value and the corresponding threshold. When the insulation resistance value is greater than or equal to the insulation resistance threshold and the electromagnetic interference amplitude is greater than the electromagnetic interference amplitude threshold, an electromagnetic interference abnormality alarm signal is output, indicating the approximate location of the interference source and the magnitude of the amplitude exceeding the standard. When the insulation resistance value is less than the insulation resistance threshold and the electromagnetic interference amplitude is greater than the electromagnetic interference amplitude threshold, a dual abnormality superposition alarm signal is output, prioritizing the marking of the insulation fault location and simultaneously attaching electromagnetic interference abnormality information; When the insulation resistance value is less than the insulation resistance threshold and the electromagnetic interference amplitude is less than or equal to the electromagnetic interference amplitude threshold, an insulation fault-type abnormal alarm signal is output, highlighting the precise location of the insulation fault, the difference between the actual insulation resistance value and the threshold, and indicating that the electromagnetic interference status is normal.

5. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 1 or 2, characterized in that, The integrated control module is configured to calculate the power output ratio by combining battery and auxiliary energy parameters, including: The integrated control module is also configured to establish a power output ratio calculation equation, with input parameters including operating condition range, task level, battery SOC value, upper limit of battery output power, and auxiliary energy output capability. The integrated control module is also configured to construct the calculation equations as follows: engine output ratio equals base ratio multiplied by operating condition coefficient multiplied by task coefficient, motor output ratio equals the difference between one and the engine output ratio multiplied by SOC coefficient, and auxiliary energy output ratio equals redundancy demand coefficient multiplied by task level coefficient. The integrated control module is also configured to preset operating condition coefficients for different operating condition ranges, task coefficients for different task levels, and SOC coefficients for different SOC values. The integrated control module is also configured to output the real-time output power ratio of the engine, motor, and auxiliary energy to ensure that the total output power matches the load demand and does not exceed the output limit of each energy source.

6. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 5, characterized in that, When the integrated control module is configured to set power output ratio adjustment rules, it includes: The integrated control module is also configured to adjust at a set ratio time interval, triggering adjustments at fixed time intervals or according to the load change magnitude. The integrated control module is also configured to immediately trigger a proportional adjustment signal when the load demand change exceeds a preset threshold, without waiting for a fixed interval. The integrated control module is also configured to follow the principle of smooth power transition during the adjustment process, and to limit the adjustment range of each energy output ratio in a single instance to no more than the preset maximum value; The integrated control module is also configured to record the operating conditions, tasks, loads, and output ratios of each energy source for each adjustment, forming an adjustment log.

7. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 6, characterized in that, When the integrated control module is configured to generate charge / discharge thresholds based on temperature and battery cycle count, it includes: The integrated control module is also configured to establish a charging and discharging threshold correlation equation, with the input parameters being real-time temperature and cumulative battery cycle count, and the output parameters being the upper charging threshold and the lower discharging threshold. The integrated control module is also configured to have a built-in temperature coefficient and cycle number coefficient in the equation. The lower the temperature, the lower the upper limit threshold for charging, and the more cycles, the higher the lower limit threshold for discharging. The integrated control module is also configured to receive power allocation results, and when the motor is in the regenerative power generation state, raise the upper limit charging threshold to the first upper limit charging threshold; when the task requirement is a high load task requirement, relax the lower limit discharging threshold to the first lower limit discharging threshold. The integrated control module is also configured to record the triggering conditions, adjustment range, and adjusted battery operating data for threshold adjustment, and feed them back to the identification and monitoring module for parameter updates.

8. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 2, characterized in that, When the integrated control module is configured to determine power supply priority based on load parameters and task level, it includes: The integrated control module is also configured to divide the load parameters into core power load parameters and auxiliary load parameters. The core power load parameters include power demand and start-up sequence, while the auxiliary load parameters include type and running priority. The integrated control module is also configured to establish matching rules: under high task level, the core power load has the highest priority for power supply, and auxiliary loads are sorted according to their relevance to the operation; under low task level, the priority of unnecessary auxiliary loads can be reduced; under medium task level, it can be flexibly adapted. If the operation scenario is close to a high-level task, it will be executed according to the high-level task rules; if it is close to a low-level task, it can be adjusted with reference to the low-level task rules. Among them, high task level corresponds to level four and level five tasks, low task level corresponds to level one and level two tasks, and medium task level corresponds to level three tasks. The integrated control module is also configured to synchronously adjust the priority of auxiliary loads and prioritize cutting off the power supply to low-correlation auxiliary loads when the power output ratio is adjusted, resulting in a change in the total power supply capacity. The integrated control module is also configured to output a power supply priority sequence, which clarifies the power supply order and power outage priority of each load.

9. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 4, characterized in that, When the identification and monitoring module is configured to output identification results and abnormal alarm signals, it includes: The identification and monitoring module is also configured to include the identification results, including real-time operating condition range, task level, and characteristic parameter deviation value, and to package and transmit them to the integrated control module in a fixed format. The identification and monitoring module is also configured to classify abnormal alarm signals according to their severity: Level 1 alarm corresponds to slight electromagnetic interference, Level 2 alarm corresponds to slight deviation in insulation resistance, and Level 3 alarm corresponds to insulation fault, strong electromagnetic interference, and superposition of double abnormalities. The identification and monitoring module is also configured such that first-level and second-level alarms are only transmitted to the integrated control module for parameter adjustment, while third-level alarms are simultaneously transmitted to the integrated control module and the loop switching verification module. The identification and monitoring module is also configured to include the fault occurrence time, location, and parameter deviation data with the alarm signal, facilitating subsequent tracing and processing.

10. The multi-source hybrid power and intelligent power management system for special vehicles according to claim 9, characterized in that, When the integrated control module is configured to receive the identification result and alarm signal and output the control signal, it includes: The integrated control module is also configured to, after receiving the identification result, first verify the integrity and validity of the data, and if the data is invalid, it will be fed back to the data acquisition and processing module for re-acquisition. The integrated control module is also configured to reduce the abnormal impact by adjusting the power output ratio or charging / discharging threshold when receiving first-level or second-level alarm signals. Upon receiving a Level 3 alarm signal, the circuit switching trigger signal is immediately output to the circuit switching verification module. The integrated control module is also configured to include a power output ratio command, a charge / discharge threshold command, and a power supply priority command in the control signal, specifying the execution unit, execution parameters, and execution time limit. The integrated control module is also configured to receive feedback results from the loop switching verification module. If the switching is successful, the current control parameters are maintained; if it fails, an emergency control scheme is activated.

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