A method for intelligent management of capacitor energy storage

Abstract

The application discloses a kind of capacitive energy storage intelligent management methods, it is related to capacitive energy storage management technical field, including the following steps, the charge-discharge process of vehicle-mounted capacitor is divided into multiple dynamic charging intervals, management strategy is formulated for each dynamic charging interval by iterative calculation, the optimal threshold sequence of capacitor charge-discharge corresponding to each dynamic charging interval is obtained, the dynamic charging interval where it is located is identified during the driving process of electric vehicle, and according to capacitor charge-discharge optimal threshold sequence, the charge-discharge behavior of vehicle-mounted capacitor is dynamically regulated and managed, by dividing dynamic charging interval, in combination with capacitor health state, battery cycle number and environmental temperature correction interval boundary, with the aid of energy recovery efficiency data in braking process optimization management strategy, to solve optimal charge-discharge threshold by immune genetic algorithm, motor inefficient interval preferentially discharges, cooperates battery state of charge closed loop to prevent battery from overcharge or overdischarge phenomenon, synergistic optimization performance, improve power system stability and economy.

Description

Technical Field

[0001] This invention relates to the field of capacitor energy storage management technology, and in particular to an intelligent management method for capacitor energy storage. Background Technology

[0002] In recent years, as electric vehicles have developed towards higher range and higher power performance, on-board capacitors have become core energy storage components for optimizing braking energy recovery efficiency, alleviating the high-load power pressure on motors, and protecting on-board batteries due to their advantages of high power density, fast charging and discharging response, and long cycle life. The intelligent design of their energy storage management methods directly determines the overall vehicle energy consumption control effect, power system stability performance, and the service life of key components, thus becoming one of the core directions for method research and development in the field of new energy vehicles.

[0003] Existing management methods suffer from insufficient optimization dimensions in setting charge and discharge thresholds: they either rely on empirical values ​​to set threshold parameters or use simple algorithms for local optimization, failing to build a complete optimization system with maximizing capacitor cycle life as the core objective. They also fail to fully integrate the coupling constraints of battery power and capacitor power, as well as the constraint of maximizing energy recovery efficiency, in designing the threshold calculation logic. Furthermore, they lack methods to analyze the impact of different operating conditions on motor efficiency using motor efficiency MAP charts to adjust charge and discharge priorities. In particular, they fail to establish a targeted priority discharge mechanism in the inefficient range of low-speed, high-load motors. These deficiencies in management methods can easily lead to problems such as mismatch between charge and discharge power and actual demand, battery overcharging and over-discharging, and motor efficiency loss. Summary of the Invention

[0004] The technical problem solved by this invention is that existing management methods have insufficient optimization dimensions in the setting of charge and discharge thresholds. They either rely on empirical values ​​to set threshold parameters or use simple algorithms for local optimization. They do not build a complete optimization system with maximizing capacitor cycle life as the core objective, nor do they fully integrate the coupling constraints of battery power and capacitor power and the constraints of maximizing energy recovery efficiency to design the threshold calculation logic. Furthermore, they lack a method to analyze the impact of different operating conditions on motor efficiency by combining motor efficiency MAP charts to adjust the charging and discharging priority. In particular, they have not established a targeted priority discharge mechanism in the inefficient range of low speed and high load of the motor. This deficiency in management methods can easily lead to problems such as mismatch between charging and discharging power and actual demand, overcharging and over-discharging of the battery, and loss of motor efficiency.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for intelligent management of capacitor energy storage, comprising the following steps:

[0006] Step S100: Divide the charging and discharging process of the vehicle capacitor into multiple dynamic charging intervals;

[0007] Step S200: By iteratively calculating, a management strategy is formulated for each dynamic charging interval, and the optimal threshold sequence for capacitor charging and discharging corresponding to each dynamic charging interval is obtained.

[0008] Step S300: During the operation of the electric vehicle, the dynamic charging zone is identified, and the charging and discharging behavior of the on-board capacitor is dynamically controlled and managed according to the optimal charging and discharging threshold sequence of the capacitor.

[0009] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, the following steps are taken: collecting the operating status parameters of the on-board capacitor, the operating condition parameters of the electric vehicle, and the status parameters of the on-board battery.

[0010] The operating status parameters include capacitor voltage, capacitor current, capacitor temperature, and capacitor health status.

[0011] The operating parameters include vehicle speed, brake trigger signal, motor power demand signal, motor load, and ambient temperature.

[0012] The state parameters of the vehicle battery include the number of battery cycles and the state of charge of the battery.

[0013] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, the dynamic charging interval refers to a charging and discharging management unit divided based on the operating parameters of the electric vehicle and the operating status parameters of the capacitor.

[0014] Based on the vehicle speed, the vehicle speed is divided into multiple preset speed ranges, and each preset speed range corresponds to a dynamic charging range.

[0015] The trigger time of the braking event is determined based on the braking trigger signal. An independent dynamic charging interval is formed with the trigger time of the braking event as the starting point and the end time of the braking event as the ending point.

[0016] Based on the capacitor health status, the number of battery cycles, and the ambient temperature, the boundary thresholds of the preset vehicle speed range and the boundary thresholds of the independent dynamic charging range are dynamically adjusted.

[0017] The independent dynamic charging zones need to collect energy recovery efficiency data synchronously, which will be used to optimize the charging and discharging thresholds when formulating management strategies for each dynamic charging zone.

[0018] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, step S200 includes the following sub-steps:

[0019] The management strategy refers to the rules for regulating the charging and discharging behavior of the capacitor based on the charging and discharging threshold within the corresponding dynamic charging range.

[0020] The charging and discharging thresholds of the capacitor include a charging start threshold, a charging stop threshold, a discharging start threshold, a discharging stop threshold, and a charging and discharging power limit threshold.

[0021] The rules include:

[0022] Based on the matching relationship between the operating status parameters and the charging start threshold, charging stop threshold, discharging start threshold, and discharging stop threshold, the start or stop of the charging and discharging behavior is determined.

[0023] Based on the matching relationship between the motor power demand signal and the charging and discharging power limit threshold, the power of charging and discharging behavior is limited.

[0024] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, step S200 further includes the following sub-steps:

[0025] For each of the aforementioned dynamic charging intervals, an initialization operation is performed;

[0026] The initialization operation includes generating a population of candidate strategies;

[0027] The candidate strategy population consists of multiple candidate strategies, and the candidate strategy population is adapted to the dynamic charging range and includes the charging and discharging threshold of the capacitor.

[0028] The candidate strategy population is the candidate sequence of capacitor charge and discharge thresholds corresponding to the dynamic charging interval.

[0029] With maximizing the cycle life of the capacitor as the optimization objective, the cycle life of the capacitor is used as the fitness evaluation criterion for the immune genetic algorithm.

[0030] The optimization constraints are formed by combining the coupling constraints of battery power and capacitor power with the constraint of maximizing energy recovery efficiency. The fitness of each candidate strategy in the candidate strategy population is calculated based on the optimization constraints.

[0031] The coupling constraints between battery power and capacitor power include the safe range of the state of charge of the vehicle battery and the upper limit of the motor power demand signal.

[0032] The energy recovery efficiency maximization constraint is to ensure the optimal efficiency of the braking energy recovery process by constraining the charging and discharging thresholds.

[0033] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, step S200 further includes the following sub-steps:

[0034] The candidate strategy population is subjected to immune selection, crossover, and mutation operations using an immune genetic algorithm to generate a new candidate strategy population corresponding to the dynamic charging interval.

[0035] Repeat the calculation of fitness and the immune selection, crossover and mutation operations for multiple iterations until an optimal candidate strategy that satisfies the optimization objective and optimization constraints appears in the candidate strategy population.

[0036] The threshold sequence of the optimal candidate strategy is determined as the optimal threshold sequence for capacitor charging and discharging corresponding to the dynamic charging interval, thus completing the formulation of the management strategy for the interval.

[0037] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, step S300 includes the following sub-steps:

[0038] Collect operating parameters of electric vehicles, operating status parameters of on-board capacitors, and status parameters of on-board batteries.

[0039] The vehicle speed is matched to a preset speed range after dynamic correction based on the capacitor health status, battery cycle count, and ambient temperature, or the vehicle speed is determined based on the braking trigger signal to determine whether it is in an independent dynamic charging range formed by the braking event trigger time as the starting point and the braking event end time as the ending point, and the dynamic charging range is determined.

[0040] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, step S300 further includes the following sub-steps:

[0041] Call the optimal capacitor charge / discharge threshold sequence corresponding to the dynamic charging interval;

[0042] By combining the motor efficiency MAP chart, we analyze the impact of different capacitor-based charging and discharging threshold management strategies on motor efficiency under operating conditions and predicted operating conditions.

[0043] Based on the comparison results between the capacitor voltage and the charging start threshold, charging stop threshold, discharging start threshold, and discharging stop threshold in the optimal capacitor charging and discharging threshold sequence, and combined with the matching relationship between the motor power demand signal and the charging and discharging power limit threshold in the optimal capacitor charging and discharging threshold sequence, the charging or discharging operation of the on-board capacitor is triggered.

[0044] The charging operation is triggered by:

[0045] A charging operation is triggered if and only if the capacitor voltage is lower than the charging start threshold and the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold.

[0046] The charging operation will stop immediately when the capacitor voltage reaches the charging stop threshold.

[0047] The triggering of the discharge operation includes:

[0048] Discharge operation is triggered if and only if the capacitor voltage is higher than the discharge start threshold and the power value corresponding to the motor power demand signal does not exceed the charge / discharge power limit threshold.

[0049] The discharge operation should be stopped immediately when the capacitor voltage drops to the discharge stop threshold.

[0050] The comparison results include:

[0051] The charging start condition is met when the capacitor voltage is lower than the charging start threshold.

[0052] The charging stop condition is met when the capacitor voltage reaches the charging stop threshold.

[0053] The discharge start condition is met when the capacitor voltage is higher than the discharge start threshold.

[0054] The discharge stop condition is met when the capacitor voltage drops to the discharge stop threshold.

[0055] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, the matching relationship includes:

[0056] The power matching condition is met when the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold.

[0057] When the power value corresponding to the motor power demand signal is exceeded, the upper limit shall be the charging and discharging power limit threshold.

[0058] When the motor speed is in the low speed range and the motor load is in the high load range, the capacitor discharge is prioritized to replenish power. At this time, even if the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold, the discharge operation is still triggered first. The discharge operation when the motor speed is in the low speed range and the motor load is in the high load range has a higher priority than the normal discharge scenario.

[0059] The motor's speed is in the low-speed range and the motor's load is in the high-load range, corresponding to the inefficient interval in the motor efficiency MAP chart.

[0060] As a preferred embodiment of the intelligent management method for capacitor energy storage described in this invention, the state of charge of the vehicle battery is monitored during the charging and discharging process.

[0061] If the state of charge exceeds the safe range of the state of charge, when the state of charge is higher than the upper limit of the safe range of the state of charge, the charging power of the capacitor is reduced to within the charging and discharging power limit threshold and does not cause the battery to be overcharged. The charging power is the actual power of the capacitor when it is charging and is constrained by the charging and discharging power limit threshold.

[0062] When the state of charge is lower than the lower limit of the safe state of charge range, the capacitor discharge power is reduced to within the charging and discharging power limit threshold without causing the battery to be over-discharged, so as to meet the coupling constraint of the battery power and the capacitor power and realize the closed-loop control of the capacitor charging and discharging behavior. The discharge power is the actual power when the capacitor is discharging, which is constrained by the charging and discharging power limit threshold.

[0063] The beneficial effects of this invention are as follows: By dynamically dividing the charging interval and combining the boundary threshold correction method with capacitor health status, on-board battery cycle count, and ambient temperature, the adaptability of the charging and discharging management unit to complex operating conditions such as vehicle speed and braking is greatly improved. At the same time, energy recovery data in the braking interval is collected to provide accurate basis for management strategy optimization. The threshold sequence is iteratively optimized using an immune genetic algorithm with the goal of maximizing capacitor cycle life. The battery-capacitor power coupling constraint and energy recovery constraint are integrated to effectively extend capacitor life. A low-efficiency interval priority discharge mechanism is established by combining the motor efficiency MAP chart to reduce motor energy consumption. With the battery SOC closed-loop control, overcharging and over-discharging are avoided. Overall, the energy recovery efficiency, component life and motor efficiency are synergistically optimized, improving the operational stability and economy of the electric vehicle power system. Attached Figure Description

[0064] Figure 1 This is a flowchart illustrating the steps of an intelligent management method for capacitor energy storage provided in one embodiment of the present invention. Detailed Implementation

[0065] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0066] Example, refer to Figure 1 As an embodiment of the present invention, a smart management method for capacitor energy storage is provided, comprising the following steps:

[0067] Step S100: Divide the charging and discharging process of the vehicle capacitor into multiple dynamic charging intervals;

[0068] Step S200: By iteratively calculating, a management strategy is formulated for each dynamic charging interval, and the optimal threshold sequence for capacitor charging and discharging corresponding to each dynamic charging interval is obtained.

[0069] Step S200: By iteratively calculating and formulating management strategies for each dynamic charging interval, the optimal capacitor charging and discharging threshold sequence corresponding to each dynamic charging interval is obtained.

[0070] In one embodiment, step S100 is first executed to divide the charging and discharging process of the on-board capacitor into multiple dynamic charging intervals. Then, step S200 is performed to formulate management strategies for each of the divided dynamic charging intervals through iterative calculation, thereby obtaining the optimal charging and discharging threshold sequence for the capacitor corresponding to each dynamic charging interval. Finally, in step S300, the current dynamic charging interval of the vehicle is identified in real time during the driving process of the electric vehicle, and the charging and discharging behavior of the on-board capacitor is dynamically controlled and managed according to the optimal charging and discharging threshold sequence for the capacitor corresponding to the dynamic charging interval. This achieves dynamic adaptation and precise management of the charging and discharging behavior of the on-board capacitor, effectively ensuring the capacitor's operating performance, improving energy utilization efficiency, and adapting to the complex driving conditions of the electric vehicle.

[0071] Collect the operating status parameters of the on-board capacitor, the operating condition parameters of the electric vehicle, and the status parameters of the on-board battery;

[0072] Operating status parameters include capacitor voltage, capacitor current, capacitor temperature, and capacitor health status;

[0073] Operating parameters include vehicle speed, brake trigger signal, motor power demand signal, motor load, and ambient temperature;

[0074] The state parameters of an onboard battery include the number of battery cycles and the state of charge (SCC).

[0075] Dynamic charging zone refers to a charging and discharging management unit divided based on the operating parameters of the electric vehicle and the operating status parameters of the capacitor.

[0076] Based on vehicle speed, the system is divided into multiple preset speed ranges, and each preset speed range corresponds to a dynamic charging range.

[0077] The trigger time of the braking event is determined based on the braking trigger signal. An independent dynamic charging interval is formed with the trigger time of the braking event as the starting point and the end time of the braking event as the ending point.

[0078] Based on the capacitor health status, the number of battery cycles, and the ambient temperature, the boundary thresholds of the preset vehicle speed range and the boundary thresholds of the independent dynamic charging range are dynamically adjusted.

[0079] Independent dynamic charging zones require the synchronous collection of energy recovery efficiency data, which will be used to optimize and constrain the charging and discharging thresholds when formulating management strategies for each dynamic charging zone.

[0080] In one embodiment, the operating status parameters of the on-board capacitor (including capacitor voltage, capacitor current, capacitor temperature, and capacitor health state (SOH)), the operating parameters of the electric vehicle (including vehicle speed, brake trigger signal, motor power demand signal, motor load, and ambient temperature), and the status parameters of the on-board battery (including on-board battery cycle count and on-board battery state of charge (SOC)) are considered. The dynamic charging interval refers to a charging and discharging management unit divided based on the aforementioned electric vehicle operating parameters and capacitor operating status parameters. The division methods include two types: one is based on vehicle speed, dividing into multiple preset speed intervals (e.g., 0-30km / h low-speed interval, 30-60km / h medium-speed interval, and above 60km / h high-speed interval), with each preset speed interval corresponding to a dynamic charging interval; the other is based on brake trigger... The signal determines the trigger time of the braking event. Starting from this trigger time and ending at the end time of the braking event (such as when the brake pedal is released), an independent dynamic charging zone is formed. After the zone is divided, the boundary thresholds of the preset vehicle speed zone and the boundary thresholds of the independent dynamic charging zone need to be dynamically adjusted based on the capacitor health status, the number of cycles of the vehicle battery, and the ambient temperature (e.g., in low-temperature environments below -10℃, the upper limit boundary of the low-speed zone can be appropriately lowered). At the same time, energy recovery efficiency data needs to be collected synchronously during the operation of the independent dynamic charging zone. The energy recovery efficiency data will be used to optimize and constrain the charging and discharging thresholds when formulating management strategies for each dynamic charging zone. This will ensure that the division of the dynamic charging zone is more in line with the actual operating scenario of the vehicle and provide a reliable basis for the precise control of the charging and discharging of the vehicle capacitor.

[0081] Step S200 includes the following sub-steps:

[0082] Management strategy refers to the rules for regulating the charging and discharging behavior of a capacitor based on its charging and discharging threshold within the corresponding dynamic charging range.

[0083] The charging and discharging thresholds of a capacitor include the charging start threshold, the charging stop threshold, the discharging start threshold, the discharging stop threshold, and the charging and discharging power limit threshold.

[0084] The rules include:

[0085] Based on the matching relationship between the operating status parameters and the charging start threshold, charging stop threshold, discharging start threshold, and discharging stop threshold, the start or stop of charging and discharging behavior is determined.

[0086] Based on the matching relationship between the motor power demand signal and the charging and discharging power limit threshold, the power of charging and discharging behavior is limited.

[0087] Step S200 also includes the following sub-steps:

[0088] Perform initialization operations for each dynamic charging range;

[0089] The initialization process includes generating a population of candidate policies;

[0090] The candidate strategy population consists of multiple candidate strategies, and the candidate strategy population is adapted to the dynamic charging range and includes the charging and discharging threshold of the capacitor.

[0091] The candidate strategy population consists of candidate sequences of capacitor charge and discharge thresholds corresponding to the dynamic charging interval.

[0092] With maximizing the cycle life of the capacitor as the optimization objective, the cycle life of the capacitor is used as the fitness evaluation criterion for the immune genetic algorithm.

[0093] The optimization constraints are formed by combining the coupling constraints of battery power and capacitor power with the constraint of maximizing energy recovery efficiency. The fitness of each candidate strategy in the candidate strategy population is calculated based on the optimization constraints.

[0094] The coupling constraints between battery power and capacitor power include the safe range of the state of charge of the vehicle battery and the upper limit of the motor power demand signal;

[0095] The energy recovery efficiency maximization constraint is to ensure the optimal efficiency of the braking energy recovery process by constraining the charging and discharging thresholds.

[0096] Step S200 also includes the following sub-steps:

[0097] The candidate strategy population is subjected to immune selection, crossover and mutation operations of the immune genetic algorithm to generate a new candidate strategy population corresponding to the dynamic charging interval;

[0098] Repeatedly calculate fitness and perform immune selection, crossover and mutation operations, and iterate multiple times until the optimal candidate strategy that satisfies the optimization objective and optimization constraints appears in the candidate strategy population.

[0099] The threshold sequence of the optimal candidate strategy is determined as the optimal threshold sequence for capacitor charging and discharging corresponding to the dynamic charging interval, thus completing the formulation of the management strategy for the interval.

[0100] In one embodiment, when performing step S200 to formulate a management strategy for the dynamic charging range, the management strategy is first defined as a rule for regulating charging and discharging behavior based on capacitor charging and discharging thresholds within the corresponding range. The charging and discharging thresholds include a charging start threshold (e.g., set to 2.5V, based on the capacitor's rated voltage of 3V, to avoid excessively low voltage affecting cycle life), a charging stop threshold (e.g., 2.9V, to reserve a safety margin to prevent overcharging), a discharging start threshold (e.g., 2.8V, to ensure sufficient energy output during discharging), a discharging stop threshold (e.g., 2.6V, to avoid over-discharging), and a charging and discharging power limit threshold (e.g., 5kW, not exceeding 50% of the motor's maximum power requirement of 10kW to reduce power surges). The specific rule is as follows: the start and stop of charging and discharging are determined based on the matching relationship between capacitor operating status parameters (e.g., voltage) and start and stop thresholds, and the charging and discharging power is limited based on the matching relationship between the motor power demand signal and the power limit threshold.

[0101] Subsequently, an initialization operation is performed for each dynamic charging interval, generating a population of candidate strategies (i.e., a candidate sequence of capacitor charging and discharging thresholds for that interval, with each candidate strategy including the specific values ​​of the five threshold categories mentioned above). With maximizing capacitor cycle life as the optimization objective, cycle life is used as the fitness evaluation criterion for the immune genetic algorithm. Simultaneously, the fitness of each candidate strategy is calculated by combining optimization constraints (including coupled constraints between battery power and capacitor power, such as the safe range of onboard battery state of charge (20%-80%) and the upper limit of motor power demand signal (10kW); and the constraint of maximizing energy recovery efficiency, ensuring optimal energy recovery efficiency during the braking interval through threshold constraints).

[0102] Subsequently, immune selection, crossover, and mutation operations are performed on the candidate strategy population (e.g., crossover of the top 30% of strategies with fitness, and random threshold fine-tuning mutation of the remaining 10%) to generate a new population. Fitness calculation and immune operation iterations are repeated (e.g., 50 iterations) until an optimal candidate strategy that meets the optimization objective and constraints emerges. Its threshold sequence is then determined as the optimal capacitor charging and discharging threshold sequence for that interval, completing the management strategy formulation. This process allows the charging and discharging thresholds for each interval to accurately adapt to scenario requirements. For example, after optimization, the energy recovery efficiency in the braking interval is improved, while the capacitor cycle life is extended, achieving a balance between lifespan and efficiency.

[0103] Step S300 includes the following sub-steps:

[0104] Collect operating parameters of electric vehicles, operating status parameters of on-board capacitors, and status parameters of on-board batteries.

[0105] The vehicle's speed is matched to a preset speed range after dynamic correction based on capacitor health status, battery cycle count, and ambient temperature, or it is determined whether it is within an independent dynamic charging range formed by the braking event triggering time and the braking event ending time based on the braking trigger signal.

[0106] Step S300 also includes the following sub-steps:

[0107] Call the optimal capacitor charging and discharging threshold sequence corresponding to the dynamic charging interval;

[0108] By combining the motor efficiency MAP chart, we analyze the impact of different capacitor-based charging and discharging threshold management strategies on motor efficiency under operating conditions and predicted operating conditions.

[0109] Based on the comparison results between the capacitor voltage and the charging start threshold, charging stop threshold, discharging start threshold and discharging stop threshold in the optimal capacitor charging and discharging threshold sequence, and combined with the matching relationship between the motor power demand signal and the charging and discharging power limit threshold in the optimal capacitor charging and discharging threshold sequence, the charging or discharging operation of the on-board capacitor is triggered.

[0110] The charging operation is triggered by:

[0111] A charging operation is triggered if and only if the capacitor voltage is lower than the charging start threshold and the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold.

[0112] The charging operation will stop immediately when the capacitor voltage reaches the charging stop threshold.

[0113] The triggering of the discharge operation includes:

[0114] Discharge operation is triggered if and only if the capacitor voltage is higher than the discharge start threshold and the power value corresponding to the motor power demand signal does not exceed the charge / discharge power limit threshold.

[0115] The discharge operation should be stopped immediately when the capacitor voltage drops to the discharge stop threshold.

[0116] The comparison results include:

[0117] The charging start condition is met when the capacitor voltage is below the charging start threshold.

[0118] The charging stop condition is met when the capacitor voltage reaches the charging stop threshold.

[0119] The discharge start condition is met when the capacitor voltage is higher than the discharge start threshold.

[0120] The discharge stop condition is met when the capacitor voltage drops to the discharge stop threshold.

[0121] Matching relationships include:

[0122] The power matching condition is met when the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold.

[0123] When the power value corresponding to the motor power demand signal is exceeded, the upper limit is the charging and discharging power limit threshold.

[0124] When the motor speed is in the low speed range and the motor load is in the high load range, the capacitor discharge is prioritized to replenish power. At this time, even if the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold, the discharge operation is still triggered first. The discharge operation when the motor speed is in the low speed range and the motor load is in the high load range has a higher priority than the normal discharge scenario.

[0125] When the motor speed is in the low-speed range and the motor load is in the high-load range, it corresponds to the inefficient range in the motor efficiency MAP chart.

[0126] In one embodiment, when performing step S300 to dynamically regulate the charging and discharging behavior of the on-board capacitor, three types of key parameters are first collected: the operating parameters of the electric vehicle (including vehicle speed, braking trigger signal, motor power demand signal, motor load, and ambient temperature), the operating status parameters of the on-board capacitor (including capacitor voltage, capacitor current, capacitor temperature, and capacitor health status), and the status parameters of the on-board battery (including the number of on-board battery cycles and state of charge). Then, the current dynamic charging interval is determined. If the judgment is based on vehicle speed, a preset vehicle speed interval (such as the 0-30km / h low speed interval, 30-60km / h medium speed interval, and above 60km / h high speed interval) corrected by capacitor health status, on-board battery cycle count, and ambient temperature is required. When the ambient temperature is below -10℃, the upper limit of the low speed interval is corrected to 25km / h. If the judgment is based on braking signal, it is necessary to determine whether it is in an independent dynamic charging interval with the braking trigger time as the starting point and the braking end time (such as the moment the brake pedal is released) as the ending point, to ensure that the interval identification accurately matches the actual operating scenario of the vehicle.

[0127] Once the charging range is determined, the optimal charging and discharging threshold sequence corresponding to that dynamic charging range is called (such as the previously set charging start threshold of 2.5V, charging stop threshold of 2.9V, discharging start threshold of 2.8V, discharging stop threshold of 2.6V, and charging and discharging power limit threshold of 5kW). At the same time, analysis is carried out in conjunction with the motor efficiency MAP. By reading the current motor speed (e.g., below 1000rpm is the low speed range), motor load (e.g., above 80% is the high load range), and the predicted operating parameters for the next stage, the impact of different charging and discharging threshold management strategies on motor efficiency is analyzed. For example, in the inefficient range of low speed and high load (speed less than 1000rpm, load greater than 80%), by optimizing the threshold to allow the capacitor to discharge first to replenish power, the motor energy consumption in this range can be reduced by 8%, improving the overall vehicle energy utilization efficiency.

[0128] Based on the above analysis, the charging and discharging operations of the on-board capacitor are triggered. The standard triggering rules require simultaneous fulfillment of voltage and power conditions: When charging is triggered, the capacitor voltage must be below the charging start threshold of 2.5V, and the power value corresponding to the motor power demand signal must not exceed the charging / discharging power limit threshold of 5kW. Charging stops immediately when the capacitor voltage reaches the charging stop threshold of 2.9V. When discharging is triggered, the capacitor voltage must be above the discharging start threshold of 2.8V, and the power value corresponding to the motor power demand signal must not exceed the charging / discharging power limit threshold of 5kW. Discharging stops immediately when the capacitor voltage drops to the discharging stop threshold of 2.6V. In special scenarios, if the motor is in a low-speed range (speed less than 1000rpm) and the load is in a high-load range (load greater than 80%), this scenario corresponds to the inefficient range in the motor efficiency MAP. In this case, priority is given to controlling capacitor discharge to replenish power. Even if the motor power demand does not exceed the 5kW power limit threshold, the discharging operation is still triggered first, and the discharging priority in this scenario is higher than in the regular discharging scenario. Through this dynamic control logic, while ensuring the safe operation of the capacitor, the energy recovery efficiency in the braking range can be improved, the capacitor cycle life extended, and a balance between vehicle performance and component lifespan can be achieved.

[0129] During charging and discharging, the state of charge of the vehicle battery is monitored;

[0130] If the state of charge exceeds the safe range of the state of charge, when the state of charge is higher than the upper limit of the safe range of the state of charge, the charging power of the capacitor is reduced to within the charging and discharging power limit threshold and does not cause the battery to be overcharged. The charging power is the actual power of the capacitor when it is charging, which is constrained by the charging and discharging power limit threshold.

[0131] When the state of charge is below the lower limit of the safe state of charge range, the capacitor discharge power is reduced to within the charge and discharge power limit threshold without causing the battery to be over-discharged, so as to meet the coupling constraints of battery power and capacitor power and realize closed-loop control of capacitor charge and discharge behavior. The discharge power is the actual power of the capacitor during discharge, which is constrained by the charge and discharge power limit threshold.

[0132] In one embodiment, during the charging and discharging of the vehicle capacitor, the state of charge of the vehicle battery needs to be monitored in real time. The safe range of the state of charge of the vehicle battery is the 20%-80% range set above (this range is set based on the requirement of maximizing the battery cycle life, which can effectively avoid battery capacity decay and shortened life caused by overcharging and over-discharging). If the vehicle battery's state of charge (SOC) is detected to be outside the safe range, the capacitor power should be dynamically adjusted according to the following rules: When the SOC is above 80% of the upper limit of the safe range, reduce the actual charging power of the capacitor (i.e., the real-time power during capacitor charging, subject to the previously set 5kW charging / discharging power limit threshold), for example, from 5kW to 3kW, to ensure that the adjusted charging power is within the 5kW threshold range without causing battery overcharging (e.g., avoiding the battery voltage from exceeding 1.1 times its rated voltage); When the SOC is below 20% of the lower limit of the safe range, reduce the actual discharging power of the capacitor (i.e., the real-time power during capacitor discharging, also subject to the 5kW charging / discharging power limit threshold), for example, from 5kW to 2kW, to ensure that the adjusted discharging power is within the 5kW threshold range without causing battery over-discharging (e.g., avoiding the battery voltage from falling below 0.9 times its rated voltage). This dynamic adjustment logic strictly conforms to the coupling constraints of battery power and capacitor power, realizing closed-loop control of capacitor charging and discharging behavior. Verified under actual working conditions, this method can extend the cycle life of the vehicle battery, while ensuring the safety and stability of the capacitor charging and discharging process, and avoiding the impact of abnormal battery status on the vehicle's energy supply.

[0133] This invention significantly improves the adaptability of the charging and discharging management unit to complex operating conditions such as vehicle speed and braking by dynamically dividing charging zones and combining methods such as capacitor health status, on-board battery cycle count, and ambient temperature to correct boundary thresholds. At the same time, it collects energy recovery data in the braking zone to provide accurate basis for management strategy optimization. It uses an immune genetic algorithm to iteratively optimize the threshold sequence with the goal of maximizing capacitor cycle life. It integrates battery-capacitor power coupling constraints and energy recovery constraints to effectively extend capacitor life. It establishes a priority discharge mechanism for inefficient zones by combining motor efficiency MAP chart to reduce motor energy consumption. With the help of closed-loop control of battery SOC, it avoids overcharging and over-discharging. Overall, it achieves synergistic optimization of energy recovery efficiency, component life and motor efficiency, and improves the operational stability and economy of electric vehicle power system.

[0134] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. 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.

[0135] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for intelligent management of capacitor energy storage, characterized in that, Includes the following steps: Step S100: Divide the charging and discharging process of the vehicle capacitor into multiple dynamic charging intervals; Step S200: By iteratively calculating, a management strategy is formulated for each dynamic charging interval, and the optimal threshold sequence for capacitor charging and discharging corresponding to each dynamic charging interval is obtained. Step S300: During the operation of the electric vehicle, the dynamic charging zone is identified, and the charging and discharging behavior of the on-board capacitor is dynamically controlled and managed according to the optimal charging and discharging threshold sequence of the capacitor. Step S200 includes the following sub-steps: The management strategy refers to the rules for regulating the charging and discharging behavior of the capacitor based on the charging and discharging threshold within the corresponding dynamic charging range. The charging and discharging thresholds of the capacitor include a charging start threshold, a charging stop threshold, a discharging start threshold, a discharging stop threshold, and a charging and discharging power limit threshold. The rules include: Based on the matching relationship between the operating status parameters and the charging start threshold, charging stop threshold, discharging start threshold, and discharging stop threshold, the start or stop of charging and discharging behavior is determined. Based on the matching relationship between the motor power demand signal and the charging and discharging power limit threshold, the power of charging and discharging behavior is limited; Step S200 also includes the following sub-steps: For each of the aforementioned dynamic charging intervals, an initialization operation is performed; The initialization operation includes generating a population of candidate strategies; The candidate strategy population consists of multiple candidate strategies, and the candidate strategy population is adapted to the dynamic charging range and includes the charging and discharging threshold of the capacitor. The candidate strategy population is the candidate sequence of capacitor charge and discharge thresholds corresponding to the dynamic charging interval. With maximizing the cycle life of the capacitor as the optimization objective, the cycle life of the capacitor is used as the fitness evaluation criterion for the immune genetic algorithm. The optimization constraints are formed by combining the coupling constraints of battery power and capacitor power with the constraint of maximizing energy recovery efficiency. The fitness of each candidate strategy in the candidate strategy population is calculated based on the optimization constraints. The coupling constraints between battery power and capacitor power include the safe range of the state of charge of the vehicle battery and the upper limit of the motor power demand signal. The energy recovery efficiency maximization constraint is to ensure the optimal efficiency of the braking energy recovery process by constraining the charging and discharging thresholds.

2. The intelligent management method for capacitor energy storage as described in claim 1, characterized in that: The operating status parameters of the on-board capacitor, the operating condition parameters of the electric vehicle, and the status parameters of the on-board battery are collected. The operating status parameters include capacitor voltage, capacitor current, capacitor temperature, and capacitor health status. The operating parameters include vehicle speed, brake trigger signal, motor power demand signal, motor load, and ambient temperature. The state parameters of the vehicle battery include the number of battery cycles and the state of charge of the battery.

3. The intelligent management method for capacitor energy storage as described in claim 2, characterized in that: The dynamic charging zone refers to the charging and discharging management unit divided based on the operating parameters of the electric vehicle and the operating status parameters of the capacitor. Based on the vehicle speed, the vehicle speed is divided into multiple preset speed ranges, and each preset speed range corresponds to a dynamic charging range. The trigger time of the braking event is determined based on the braking trigger signal. An independent dynamic charging interval is formed with the trigger time of the braking event as the starting point and the end time of the braking event as the ending point. Based on the capacitor health status, the number of battery cycles, and the ambient temperature, the boundary thresholds of the preset vehicle speed range and the boundary thresholds of the independent dynamic charging range are dynamically adjusted. The independent dynamic charging zones need to collect energy recovery efficiency data synchronously, which will be used to optimize the charging and discharging thresholds when formulating management strategies for each dynamic charging zone.

4. The intelligent management method for capacitor energy storage as described in claim 3, characterized in that: Step S200 also includes the following sub-steps: The candidate strategy population is subjected to immune selection, crossover, and mutation operations using an immune genetic algorithm to generate a new candidate strategy population corresponding to the dynamic charging interval. Repeat the calculation of fitness and the immune selection, crossover and mutation operations for multiple iterations until an optimal candidate strategy that satisfies the optimization objective and optimization constraints appears in the candidate strategy population. The threshold sequence of the optimal candidate strategy is determined as the optimal threshold sequence for capacitor charging and discharging corresponding to the dynamic charging interval, thus completing the formulation of the management strategy for the interval.

5. The intelligent management method for capacitor energy storage as described in claim 4, characterized in that: Step S300 includes the following sub-steps: Collect operating parameters of electric vehicles, operating status parameters of on-board capacitors, and status parameters of on-board batteries. The vehicle speed is matched to a preset speed range after dynamic correction based on the capacitor health status, battery cycle count, and ambient temperature, or the vehicle speed is determined based on the braking trigger signal to determine whether it is in an independent dynamic charging range formed by the braking event trigger time as the starting point and the braking event end time as the ending point, and the dynamic charging range is determined.

6. The intelligent management method for capacitor energy storage as described in claim 5, characterized in that: Step S300 further includes the following sub-steps: Call the optimal capacitor charge / discharge threshold sequence corresponding to the dynamic charging interval; By combining the motor efficiency MAP chart, we analyze the impact of different capacitor-based charging and discharging threshold management strategies on motor efficiency under operating conditions and predicted operating conditions. Based on the comparison results between the capacitor voltage and the charging start threshold, charging stop threshold, discharging start threshold, and discharging stop threshold in the optimal capacitor charging and discharging threshold sequence, and combined with the matching relationship between the motor power demand signal and the charging and discharging power limit threshold in the optimal capacitor charging and discharging threshold sequence, the charging or discharging operation of the on-board capacitor is triggered. The charging operation is triggered by: A charging operation is triggered if and only if the capacitor voltage is lower than the charging start threshold and the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold. The charging operation will stop immediately when the capacitor voltage reaches the charging stop threshold. The triggering of the discharge operation includes: Discharge operation is triggered if and only if the capacitor voltage is higher than the discharge start threshold and the power value corresponding to the motor power demand signal does not exceed the charge / discharge power limit threshold. The discharge operation should be stopped immediately when the capacitor voltage drops to the discharge stop threshold. The comparison results include: The charging start condition is met when the capacitor voltage is lower than the charging start threshold. The charging stop condition is met when the capacitor voltage reaches the charging stop threshold. The discharge start condition is met when the capacitor voltage is higher than the discharge start threshold. The discharge stop condition is met when the capacitor voltage drops to the discharge stop threshold.

7. The intelligent management method for capacitor energy storage as described in claim 6, characterized in that: The matching relationships include: The power matching condition is met when the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold. When the power value corresponding to the motor power demand signal is exceeded, the upper limit shall be the charging and discharging power limit threshold. When the motor speed is in the low speed range and the motor load is in the high load range, the capacitor discharge is prioritized to replenish power. At this time, even if the power value corresponding to the motor power demand signal does not exceed the charging and discharging power limit threshold, the discharge operation is still triggered first. The discharge operation when the motor speed is in the low speed range and the motor load is in the high load range has a higher priority than the normal discharge scenario. The motor's speed is in the low-speed range and the motor's load is in the high-load range, corresponding to the inefficient interval in the motor efficiency MAP chart.

8. The intelligent management method for capacitor energy storage as described in claim 7, characterized in that: During charging and discharging, the state of charge of the vehicle battery is monitored; If the state of charge exceeds the safe range of the state of charge, when the state of charge is higher than the upper limit of the safe range of the state of charge, the charging power of the capacitor is reduced to within the charging and discharging power limit threshold and does not cause the battery to be overcharged. The charging power is the actual power of the capacitor when it is charging and is constrained by the charging and discharging power limit threshold. When the state of charge is lower than the lower limit of the safe state of charge range, the capacitor discharge power is reduced to within the charging and discharging power limit threshold without causing the battery to be over-discharged, so as to meet the coupling constraint of the battery power and the capacitor power and realize the closed-loop control of the capacitor charging and discharging behavior. The discharge power is the actual power when the capacitor is discharging, which is constrained by the charging and discharging power limit threshold.

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