Brake system control method, electronic equipment, vehicle and storage medium

Abstract

The invention discloses a control method of a braking system, electronic equipment, a vehicle and a storage medium, and relates to the technical field of vehicles, the control method of the braking system specifically comprises the steps that the target deceleration and the actual deceleration of the vehicle are obtained, and the deceleration deviation between the target deceleration and the actual deceleration is determined; determining a target first control parameter group based on the deceleration deviation, and determining a target hydraulic pressure in combination with the target first control parameter group; the actual hydraulic pressure of the vehicle is obtained, and the hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure is determined; and a target second control parameter set is determined based on the hydraulic pressure deviation, motor demand current is determined in combination with the target second control parameter set, and a braking system of the vehicle is controlled according to the motor demand current. According to the invention, the control precision of the brake system can be obviously improved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a control method for a braking system, electronic equipment, a vehicle, and a storage medium. Background Technology

[0002] With the continuous development of the automotive industry, vehicles are placing extremely high demands on the deceleration control precision of their braking systems.

[0003] As the core solution of brake-by-wire, the EHB system (Electro-Hydraulic Brake system) can achieve precise control of vehicle deceleration by adjusting hydraulic pressure. In related technologies, the PID parameters required for adjusting the hydraulic pressure of the EHB system are usually calibrated by technicians based on experience.

[0004] However, the PID parameters calibrated by technicians based on experience are only suitable for a limited number of scenarios, making it difficult to adapt to complex road conditions. As a result, when a vehicle is in a complex road condition, it is prone to large deceleration deviations and severe hydraulic pressure overshoot, which leads to a significant reduction in the control accuracy of the EHB system. Summary of the Invention

[0005] The main objective of this application is to provide a control method for a braking system, an electronic device, a vehicle, and a storage medium, aiming to solve the technical problem of reduced control accuracy of braking systems in related technologies.

[0006] To achieve the above objectives, this application proposes a control method for a braking system, the control method comprising: Obtain the target deceleration and actual deceleration of the vehicle, and determine the deceleration deviation between the target deceleration and the actual deceleration; The first set of target control parameters is determined based on the deceleration deviation, and the target hydraulic pressure is determined in combination with the first set of target control parameters. The actual hydraulic pressure of the vehicle is obtained, and the hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure is determined. The target second control parameter set is determined based on the hydraulic pressure deviation, and the motor demand current is determined in combination with the target second control parameter set. The braking system of the vehicle is then controlled according to the motor demand current.

[0007] In one embodiment, the step of determining the first set of target control parameters based on the deceleration deviation includes: The differential of the deceleration deviation is obtained by performing differential processing on the deceleration deviation. Multiple initial first control parameter sets are determined, and a first initial fitness corresponding to each of the multiple initial first control parameter sets is determined based on the differential of the deceleration deviation and the deceleration deviation; Based on each of the first initial fitness values, the multiple initial first control parameter sets are iterated to obtain the target first control parameter set.

[0008] In one embodiment, the step of determining a plurality of initial first control parameter groups includes: Determine the preset search area and preset population size; Based on the preset population size, multiple initial first control parameter sets are determined within the preset search range.

[0009] In one embodiment, the step of iterating through the plurality of initial first control parameter sets based on each of the first initial fitness values ​​to obtain a target first control parameter set includes: Based on each of the first initial fitness, each first pioneer, each first joiner, and each first watcher are determined from multiple sets of the first initial control parameters; The first global optimal position is determined based on each of the first initial fitness values; The first global optimum position is perturbed, and the first update fitness of the perturbed first global optimum position is determined. The target first control parameter set is obtained by iterating over each of the first pioneers, each of the first joiners and each of the first watchers in combination with the first updated fitness.

[0010] In one embodiment, the step of iteratively obtaining the target first control parameter set by combining the first updated fitness with each of the first pioneers, each of the first joiners, and each of the first watchers includes: If the first updated fitness is detected to be greater than the first initial fitness of the first global optimal position, a preset decreasing inertial weight is obtained and the first global worst position is determined. The first pioneers and the first watchers are updated based on the decreasing inertia weights, and the first joiners are updated based on their respective first initial fitness, first global best position, and first global worst position. Based on the updated positions of each first trailblazer, first joiner, and first watcher, determine the updated first global optimal position and the current deceleration iteration round. If the current deceleration iteration round is detected to have reached the preset maximum iteration round, the updated first global optimal position is determined as the target first control parameter group.

[0011] In one embodiment, the step of determining the target second set of control parameters based on the hydraulic pressure deviation includes: The differential of the hydraulic pressure deviation is obtained by performing differential processing on the hydraulic pressure deviation. Multiple initial second control parameter sets are determined, and the second initial fitness corresponding to each of the multiple initial second control parameter sets is determined based on the hydraulic pressure deviation and the derivative of the hydraulic pressure deviation; Each second pioneer, each second joiner, and each second watchman are determined from among the multiple sets of said initial second control parameters based on each of the second initial fitness; The second global optimal position is determined based on each of the second initial fitness values; The target second control parameter set is obtained by iteratively processing each second pioneer, each second joiner, and each second watcher based on the second global optimal position.

[0012] In one embodiment, the step of iteratively processing each of the second pioneers, each of the second joiners, and each of the second watchmen based on the second global optimal position to obtain the target second control parameter set includes: Determine the randomly generated variable corresponding to the second global optimal position; If the randomly generated variable is detected to have reached a preset adaptive threshold, the second global optimal position is perturbed, and the second update fitness of the perturbed second global optimal position is determined. If the second updated fitness is detected to be greater than the second initial fitness of the second global optimal position, a preset decreasing inertial weight is obtained and the second global worst position is determined; The second pioneers and the second watchers are updated based on the preset decreasing inertia weights, and the second joiners are updated based on their respective second initial fitness, second global best position and second global worst position. Based on the updated second pioneers, second joiners, and second watchers, determine the updated second global optimal position and the current hydraulic pressure iteration round; If the current hydraulic pressure iteration round is detected to have reached the preset maximum iteration round, the updated second global optimal position is determined as the target second control parameter group.

[0013] In addition, to achieve the above objectives, this application also proposes an electronic device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the control method for the braking system as described above.

[0014] In addition, to achieve the above objectives, this application also proposes a vehicle that includes the electronic equipment described above.

[0015] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the control method of the braking system as described above.

[0016] The braking system control method provided in this application embodiment acquires the target deceleration and actual deceleration of the vehicle, and determines the deceleration deviation between the target deceleration and the actual deceleration; determines a target first control parameter set based on the deceleration deviation, and determines a target hydraulic pressure in combination with the target first control parameter set; acquires the actual hydraulic pressure of the vehicle, and determines the hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure; determines a target second control parameter set based on the hydraulic pressure deviation, and determines the motor demand current in combination with the target second control parameter set, and controls the braking system of the vehicle according to the motor demand current.

[0017] In this embodiment, if the electronic device needs to control the vehicle's braking system to complete a deceleration operation, it first obtains the target deceleration to be achieved by the vehicle. Simultaneously, the electronic device detects the vehicle to determine its actual deceleration. The electronic device then calculates the deceleration deviation between the target deceleration and the actual deceleration. Next, the electronic device processes the deceleration deviation using a preset optimization algorithm to determine a first set of target control parameters for adjusting the deceleration deviation. Then, it combines the first set of target control parameters to determine a target hydraulic pressure that can accurately adjust the deceleration deviation. Afterward, the electronic device detects the actual hydraulic pressure of the vehicle during deceleration and determines the hydraulic pressure deviation between the actual hydraulic pressure and the target hydraulic pressure. Finally, the electronic device determines a second set of target control parameters based on the hydraulic pressure deviation and, based on the second control parameters, determines the motor current required to control the braking system and reduce the hydraulic pressure deviation. The electronic device then generates a motor control command according to the motor current requirement to control the vehicle's braking system according to the motor control command.

[0018] Thus, this application solves the technical problem of reduced control accuracy of braking systems in related technologies. Specifically, this application uses a biomimetic dove algorithm to screen the first target control parameter for reducing deceleration deviation, and uses the biomimetic dove algorithm to screen and process the first target control parameter and hydraulic pressure deviation to determine the second target control parameter for reducing hydraulic pressure deviation. Based on the second target control parameter, the motor demand current for controlling the braking system is determined. This method can automatically screen deceleration PID parameters and hydraulic pressure PID parameters that match the current road conditions based on deceleration deviation and hydraulic pressure deviation without requiring technicians to calibrate PID parameters based on experience. Then, the braking system can be accurately controlled according to the deceleration PID parameters and hydraulic pressure PID parameters, significantly improving the control accuracy of the braking system. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating an embodiment of the control method for the braking system of this application.

[0022] Figure 2 This is a simplified flowchart illustrating an embodiment of the control method for the braking system of this application.

[0023] Figure 3 This is a schematic diagram of the optimization algorithm for the braking system control method of this application.

[0024] Figure 4 This is a schematic diagram of the module structure of the control device of the braking system in an embodiment of this application.

[0025] Figure 5 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the control method of the braking system in the embodiments of this application.

[0026] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0027] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0028] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0029] In this embodiment, for ease of description, the following description uses an electronic device that is internally configured with a deceleration PID controller and a hydraulic pressure PID controller, and can connect to the EHB system configured in the vehicle, as the execution subject. It can be understood that this electronic device can specifically be the ECU (Electronic Control Unit) in the vehicle.

[0030] Based on the aforementioned electronic equipment, the overall concept of the control method for the braking system of this application is presented here.

[0031] With the continuous development of the automotive industry, vehicles are placing extremely high demands on the deceleration control precision of their braking systems. The EHB system (Electro-Hydraulic Brake system), as a core solution for brake-by-wire, can achieve precise control of vehicle deceleration by adjusting hydraulic pressure. In related technologies, the PID parameters required for adjusting the hydraulic pressure in an EHB system are usually calibrated by technicians based on experience. However, the PID parameters calibrated by technicians based on experience are only suitable for a limited range of scenarios, making it difficult to adapt to complex road conditions. Thus, when a vehicle is in complex road conditions, it is prone to large deceleration deviations and severe hydraulic pressure overshoot, resulting in a significant reduction in the control precision of the EHB system.

[0032] To address the above issues, this application provides a control method for a braking system. The method includes: acquiring a target deceleration and an actual deceleration of a vehicle, and determining a deceleration deviation between the target deceleration and the actual deceleration; determining a first set of target control parameters based on the deceleration deviation, and determining a target hydraulic pressure in conjunction with the first set of target control parameters; acquiring the actual hydraulic pressure of the vehicle, and determining a hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure; determining a second set of target control parameters based on the hydraulic pressure deviation, and determining a motor demand current in conjunction with the second set of target control parameters; and controlling the braking system of the vehicle according to the motor demand current.

[0033] Thus, this application solves the technical problem of reduced control accuracy of braking systems in related technologies. Specifically, this application uses a biomimetic dove algorithm to screen the first target control parameter for reducing deceleration deviation, and uses the biomimetic dove algorithm to screen and process the first target control parameter and hydraulic pressure deviation to determine the second target control parameter for reducing hydraulic pressure deviation. Based on the second target control parameter, the motor demand current for controlling the braking system is determined. This method can automatically screen deceleration PID parameters and hydraulic pressure PID parameters that match the current road conditions based on deceleration deviation and hydraulic pressure deviation without requiring technicians to calibrate PID parameters based on experience. Then, the braking system can be accurately controlled according to the deceleration PID parameters and hydraulic pressure PID parameters, significantly improving the control accuracy of the braking system.

[0034] Based on the overall concept of the braking system control method of this application, the embodiments of this application provide a braking system control method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the control method for the braking system of this application. In this embodiment, the control method for the braking system includes steps S10 to S40: Step S10: Obtain the target deceleration and actual deceleration of the vehicle, and determine the deceleration deviation between the target deceleration and the actual deceleration; Step S20: Determine the first set of target control parameters based on the deceleration deviation, and determine the target hydraulic pressure in combination with the first set of target control parameters; It should be noted that the target deceleration is the ideal deceleration that the vehicle should achieve when the driver, inside the vehicle, depresses the brake pedal to trigger EHB system control. Furthermore, the actual deceleration is the current, real deceleration detected by the vehicle during the deceleration process. Additionally, the first set of control parameters for this target is the optimal deceleration PID parameters obtained through deceleration control optimization, including proportional parameters. Differential parameters Integral parameters It is understandable that the target first control parameter set can precisely adjust the deceleration deviation. Furthermore, the target hydraulic pressure is the braking system hydraulic pressure requirement value that the deceleration PID controller within the electronic device outputs based on the target first control parameter set, enabling the vehicle to achieve the target deceleration.

[0035] In this embodiment, when the driver depresses the brake pedal to reduce the vehicle speed, the electronic device first determines the target deceleration required by the driver based on the change in the brake pedal angle. Simultaneously, the electronic device calls the inertial measurement unit configured on the vehicle to collect longitudinal acceleration data of the vehicle body, and then determines the actual deceleration of the vehicle during the deceleration process based on the collected longitudinal acceleration data. At this time, the electronic device inputs the collected actual deceleration and target deceleration into its configured deceleration PID controller. The deceleration PID controller calculates the deceleration deviation between the target deceleration and the actual deceleration. Then, the deceleration PID controller starts the preset dove-optimized deceleration PID algorithm. The dove-optimized deceleration PID algorithm filters out the target first control parameter group that matches the deceleration deviation from the preset initial first control parameter groups, and processes the target first control parameter group and the deceleration deviation through the preset PID calculation formula to obtain the target hydraulic pressure that can reduce the deceleration deviation.

[0036] For example, please refer to Figure 2 , Figure 2 This is a simplified flowchart illustrating an embodiment of the control method for the braking system of this application, as shown below. Figure 2 As shown, when the driver depresses the brake pedal to reduce the vehicle's speed, the ECU first determines the target deceleration required by the driver based on the change in the brake pedal angle. Simultaneously, the ECU uses the vehicle's IMU (Inertial Measurement Unit) to detect the vehicle's longitudinal acceleration during braking. At the same time, the ECU uses the vehicle's wheel speed sensors to collect the front wheel speeds. Based on the wheel speeds and longitudinal acceleration, the ECU calculates the actual deceleration during braking. The ECU then inputs the target deceleration and the actual deceleration to its configured deceleration PID controller. The deceleration PID controller subtracts the target deceleration from the actual deceleration to obtain the deceleration deviation. Then, the deceleration PID controller differentiates the deceleration deviation to obtain the deceleration deviation derivative. Simultaneously, the deceleration PID controller activates a preset dove-optimized deceleration PID algorithm to iteratively optimize each initial deceleration PID parameter within the population. Based on the deceleration deviation and the deceleration deviation derivative, the fitness of each initial deceleration PID parameter after iterative optimization is determined, and finally, the target deceleration PID parameter that best matches the deceleration deviation derivative is output. The deceleration PID controller combines the deceleration deviation, the derivative of the deceleration deviation, and the target deceleration PID parameters. Input the value into the preset PID calculation formula to calculate the target hydraulic pressure that can reduce deceleration deviation.

[0037] In this way, the electronic equipment can dynamically optimize the deceleration PID parameters based on the Ikaruga optimization algorithm and deceleration deviation to obtain the optimal deceleration PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal deceleration PID parameters, which significantly improves the control accuracy of the braking system.

[0038] In one feasible implementation, the step of "determining the first set of target control parameters based on the deceleration deviation" in step S20 above may specifically include steps S201 to S203: Step S201: Differentiate the deceleration deviation to obtain the deceleration deviation derivative; Step S202: Determine multiple initial first control parameter sets, and determine the first initial fitness corresponding to each of the multiple initial first control parameter sets based on the deceleration deviation derivative and the deceleration deviation; Step S203: Iterate through the multiple initial first control parameter sets based on each of the first initial fitness values ​​to obtain the target first control parameter set.

[0039] It should be noted that this differential processing involves calculating the derivative of the deceleration deviation over fixed time intervals to obtain the rate of change of the deceleration deviation. Furthermore, the initial first control parameter set consists of unoptimized candidate deceleration PID parameters for deceleration control, and each initial first control parameter set includes a proportional parameter. Differential parameters Integral parameters It is understandable that the parameter range of the initial first control parameter group can be determined by technicians based on the braking performance of the EHB system. Similarly, the initial population size of the initial first control parameter group can be set based on the balance between search diversity and computational efficiency of the dove deceleration PID algorithm. In this embodiment, the proportional parameter in the initial first control parameter group... The value range is [0.00001, 20], and the differential parameter is... Integral parameters The value range is [0.00001, 2]. Similarly, the initial population size of the initial first control parameter group is 100, and the spatial dimension is 3. In addition, the first initial fitness is a quantitative indicator for evaluating the effect of the initial first control parameter group. It can be understood that the smaller the first initial fitness, the better the deceleration control effect of the first initial control parameter group.

[0040] In this embodiment, after determining the deceleration deviation, the deceleration PID controller first performs differentiation on the deceleration deviation to obtain the deceleration deviation derivative. Then, the deceleration PID controller starts the preset dove-optimized deceleration PID algorithm. The dove-optimized deceleration PID algorithm first determines multiple initial first control parameter sets for adjusting the deceleration deviation, and determines the first initial fitness corresponding to each of the multiple initial first control parameter sets based on the deceleration deviation derivative. Finally, the dove-optimized deceleration PID algorithm sets a first pioneer, a first joiner, and a first watcher in the multiple initial first control parameter sets according to each first initial fitness, and then performs iterative optimization based on each first pioneer, first joiner, and first watcher to obtain the target first control parameter set.

[0041] For example, after calculating the deceleration deviation, the deceleration PID controller first collects deceleration deviations within multiple detection cycles according to a preset detection period, and performs differential processing on the multiple deceleration deviations to obtain the differential deceleration deviation. Then, the deceleration PID controller calls a preset dove-optimized deceleration PID algorithm to generate 100 sets of initial deceleration PID parameters within a preset parameter range based on a multidimensional uniform random generation strategy. The dove-optimized deceleration PID algorithm then uses the initial deceleration PID parameters and the differential deceleration deviation as inputs to a preset deceleration control simulation model to simulate the deceleration control. The vehicle deceleration process over a certain time period is analyzed to obtain 100 sets of initial deceleration PID parameters, each corresponding to a first initial fitness. Finally, the Ibaraki Dove optimized deceleration PID algorithm selects the top 20% of the initial deceleration PID parameters based on their first initial fitness as pioneers, the remaining 80% as entrants, and randomly selects 20% of the pioneers and entrants as watchmen. The global optimal position is then updated for each pioneer, entrant, and watchman to obtain target deceleration PID parameters that can adjust for deceleration deviations. .

[0042] In this way, the electronic equipment can dynamically optimize the deceleration PID parameters based on the Ikaruga optimization algorithm and deceleration deviation to obtain the optimal deceleration PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal deceleration PID parameters, which significantly improves the control accuracy of the braking system.

[0043] In one feasible implementation, the step of "determining multiple initial first control parameter groups" in step S202 above may specifically include steps S2021 to S2022: Step S2021: Determine the preset search range and preset population size; Step S2022: Based on the preset population size, determine multiple initial first control parameter groups within the preset search range.

[0044] It should be noted that the preset search range is the boundary of the initial first control parameter set pre-defined based on the braking characteristics and deceleration control accuracy requirements of EHB. In this embodiment, the proportional parameter in the initial first control parameter set... The value range is [0.00001, 20], and the differential parameter is... Integral parameters The value range is [0.00001, 2]. Furthermore, the preset population size is the total number of the initial first control parameter group as preset. It is understood that a preset population size that is too small will result in a small search range, making it difficult to cover the optimal control parameter group region. Similarly, a preset population size that is too large will increase the computational load on the electronic device. In this embodiment, the initial population size of the initial first control parameter group is 100.

[0045] In this embodiment, after calculating the differential of the deceleration deviation, the deceleration PID controller first obtains the preset search range and the preset population size. Then, the deceleration PID controller starts the preset dove-optimized deceleration PID algorithm. According to the preset population size, the dove-optimized deceleration PID algorithm calls the multidimensional uniform random generation algorithm to generate multiple initial first control parameter sets with the same number as the preset population size within the preset search range.

[0046] For example, after calculating the derivative of the deceleration deviation, the deceleration PID controller first determines the pre-proportional parameter. The value range is [0.00001, 20], and the differential parameter is... Integral parameters The value range is [0.00001, 2]. Simultaneously, the deceleration PID controller determines the preset population size to be 100 groups. Then, the deceleration PID controller starts the preset dove-optimized deceleration PID algorithm, adjusting the proportional parameters using this algorithm. Differential parameters Integral parameters According to the multidimensional uniform random generation algorithm: 100 sets of initial deceleration PID parameters were obtained by mapping within the preset search range and dimensions.

[0047] Understandably, in multidimensional uniform random generation algorithms, For the first The upper limit of latitude, For the first The lower limit of latitude.

[0048] Furthermore, in this embodiment and another embodiment, the dove-optimized deceleration PID algorithm can also call a preset parameter mapping algorithm during the process of generating initial deceleration PID parameters: ; Determine the first The initial deceleration PID parameter is at the first... The components of the dimension are used to uniformly generate 100 initial deceleration PID parameters within a preset search range. This can be understood as the parameter mapping algorithm... To meet The smallest prime number, Population size.

[0049] In this way, the electronic equipment can dynamically optimize the deceleration PID parameters based on the Ikaruga optimization algorithm and deceleration deviation to obtain the optimal deceleration PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal deceleration PID parameters, which significantly improves the control accuracy of the braking system.

[0050] In one feasible implementation, step S203 above may specifically include steps S2031 to S2034: Step S2031: Based on each of the first initial fitness, determine each first pioneer, each first joiner, and each first watcher in the plurality of initial first control parameter groups; Step S2032: Determine the first global optimal position based on each of the first initial fitness values; Step S2033: Perturb the first global optimal position and determine the first update fitness of the perturbed first global optimal position; Step S2034: Combine the first updated fitness to iterate on each of the first pioneers, each of the first joiners and each of the first watchers to obtain the target first control parameter set.

[0051] It should be noted that pioneers are selected from the initial control parameter set, representing the control parameter set with the best initial fitness. The number of pioneers typically accounts for 20% of the preset population size. The role of pioneers is to explore better parameter regions; that is, to adjust towards potentially better directions based on the current global optimum, providing new optimization directions for the population. Furthermore, joiners are the remaining control parameter sets in the initial control parameter set excluding pioneers. The number of joiners typically accounts for 80% of the preset population size. The role of joiners is to balance the convergence and diversity of the population. Joiners with better fitness can autonomously fine-tune within the exploration range of pioneers, while joiners with poorer fitness move closer to the global optimum. Furthermore, the watchmen are a randomly selected subset of control parameters from the pioneers and joiners. The number of watchmen typically accounts for 20% of the preset population size. Understandably, the role of the watchmen is to prevent the algorithm from getting trapped in local optima. That is, central watchmen closer to the global optimum are responsible for actively exploring new areas, while edge watchmen farther from the global optimum are responsible for converging towards it, thus avoiding over-concentration of the population in a particular area. Additionally, the global optimum is the PID parameter with the highest initial fitness among all initial PID parameters in the current iteration. Understandably, the global optimum is the target benchmark for population optimization, and it is dynamically updated with each iteration. Furthermore, the updated fitness is the fitness recalculated after perturbing the global optimum. Understandably, this updated fitness is used to evaluate whether the perturbed global optimum is desirable; that is, if the updated fitness is less than the original initial fitness, the updated global optimum is used as the parameter set after the perturbed process.

[0052] In this embodiment, after determining the first initial fitness corresponding to each of the multiple initial control parameter groups, the Dove-Optimized Deceleration PID Algorithm first sorts the multiple initial control parameter groups based on the multiple initial fitnesss. Based on the sorting results, it determines each first explorer and each first joiner from the multiple initial control parameter groups, and randomly selects each first watcher from among the first explorers and each first joiner. Then, the Dove-Optimized Deceleration PID Algorithm determines the first global optimal position based on each initial fitness. Finally, the Dove-Optimized Deceleration PID Algorithm perturbs the first global optimal position. This determines the first update fitness corresponding to the first global optimal position after the disturbance. Finally, the dove-optimized deceleration PID algorithm judges whether the first global optimal position after the disturbance is valid based on the first update fitness. If the first global optimal position after the disturbance is determined to be valid, it iteratively optimizes each first pioneer, each first joiner, and each first watcher based on the first global optimal position after the disturbance. Then, it updates the first global optimal position after the disturbance based on the optimized first pioneer, each first joiner, and each first watcher until the number of iterations reaches the preset maximum number of iterations, and then outputs the target first control parameter set.

[0053] For example, please refer to Figure 3 , Figure 3 This is a schematic diagram of the optimization algorithm for the braking system control method of this application, as shown in the figure. Figure 3 As shown, the Dove-optimized deceleration PID algorithm, after determining the first initial fitness for each of the multiple initial deceleration PID parameters, first sorts the 100 sets of initial deceleration PID parameters in ascending order of their first initial fitness. Then, based on the sorting result, the top 20% of the initial deceleration PID parameters are designated as the first pioneers, and the remaining 80% are designated as the first joiners. From the pioneers and joiners, 20 sets of initial deceleration PID parameters are selected as the first watchers. Next, based on the sorting result, the Dove-optimized deceleration PID algorithm selects the deceleration PID parameter with the smallest first initial fitness as the first global optimum. Finally, the Dove-optimized deceleration PID algorithm obtains a preset adaptive perturbation probability. : ,in, This represents the maximum number of iterations. Meanwhile, the dove-optimized deceleration PID algorithm determines the random variable between [0,1] based on the current iteration round. The dove-optimized deceleration PID algorithm will adapt to the disturbance probability. and random variables A comparison is performed to detect adaptive perturbation probabilities. Greater than random variables In this case, the disturbance term is determined according to the preset first disturbance formula. : ,in, and For the positions of individuals in two random populations, This is the first globally optimal position; Meanwhile, the optimized deceleration PID algorithm for pigeons is based on the disturbance term. The first global optimum position is obtained by perturbing and optimizing it according to the preset second perturbation formula. : ,in, A random number between [0, 1]; At this point, the dove-optimized deceleration PID algorithm will determine the first globally optimal position after the perturbation. Substitute the values ​​into the deceleration control simulation model to determine the first globally optimal position after the disturbance. The first updated fitness is used to determine the first globally optimal position of the dove-optimized deceleration PID algorithm after the perturbation, based on the first updated fitness. If effective, update the positions of each first trailblazer, first joiner, and first watcher, thereby determining the first globally optimal position after perturbation based on the updated positions of each first trailblazer, first joiner, and first watcher. Optimize until the preset maximum number of iterations is reached, then determine the first globally optimal position as the target deceleration PID control parameter. .

[0054] In this way, the electronic equipment can dynamically optimize the deceleration PID parameters based on the Ikaruga optimization algorithm and deceleration deviation to obtain the optimal deceleration PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal deceleration PID parameters, which significantly improves the control accuracy of the braking system.

[0055] In one feasible implementation, step S2034 above may specifically include steps S20341 to S20344: Step S20341: If the first updated fitness is detected to be greater than the first initial fitness of the first global optimal position, obtain the preset decreasing inertia weight and determine the first global worst position; Step S20342: Update each of the first pioneers and each of the first watchers based on the decreasing inertia weights, and update each of the first joiners based on their respective first initial fitness, first global best position and first global worst position; Step S20343: Determine the updated first global optimal position based on the updated first pioneers, first joiners, and first watchers, and determine the current deceleration iteration round; Step S20344: If it is detected that the current deceleration iteration round has reached the preset maximum iteration round, the updated first global optimal position is determined as the target first control parameter group.

[0056] It should be noted that the decreasing inertia weight is a weight coefficient that decreases linearly with the number of iterations. It is used to adjust the exploratory and convergent nature of parameter updates. Understandably, a larger decreasing inertia weight in the initial stage increases the initial PID parameters' ability to explore new regions; similarly, a smaller decreasing inertia weight in later stages strengthens the initial PID parameters' tendency to converge towards the global optimum. Furthermore, the current deceleration iteration number is the number of iterations of the Ibaraki-Douji algorithm that have been completed since the initial deceleration PID parameters. Additionally, the maximum number of iterations is the preset maximum number of iterations to terminate the algorithm. It is understood that the specific value of this maximum number of iterations can be set by the technician according to their needs, and this application does not impose any restrictions on it.

[0057] In this embodiment, after determining the first updated fitness of the first globally optimal position after the disturbance, the dove-optimized deceleration PID algorithm first compares the first updated fitness with the first initial fitness of the first globally optimal position. If the first updated fitness is detected to be greater than the first initial fitness, the algorithm determines that the first globally optimal position after the disturbance is valid, obtains a preset decreasing inertia weight, and determines the first globally worst position corresponding to the first globally optimal position after the disturbance. Then, the deceleration PID controller updates each first pioneer and each first watcher based on the decreasing inertia weight. Simultaneously, the deceleration PID control updates each first joiner's first initial fitness. The fitness, first global optimal position, and first global worst position are updated for each first joiner. Then, the deceleration determines the updated first fitness for each first pioneer, each first watcher, and each first joiner. Based on the first fitness, the updated first global optimal position is determined. At the same time, the deceleration PID controller determines the current deceleration iteration round. Finally, the deceleration PID controller obtains the preset maximum iteration round and compares the current deceleration iteration round with the maximum iteration round. If the current iteration round is detected to have reached the maximum iteration round, the updated first global optimal position is determined as the target first control parameter set.

[0058] For example, the dove-optimized deceleration PID algorithm determines the first globally optimal position after a perturbation. After the first updated fitness, the first updated fitness is compared with the first initial fitness of the first global optimum position before the perturbation. If the first updated fitness is detected to be greater than the first initial fitness, the perturbed first global optimum position is then determined. Determined as the latest globally optimal position The worst global position is recorded based on the fitness levels after the perturbation. At this point, the dove optimized deceleration PID algorithm obtains the decreasing inertia weight corresponding to the current iteration round. : ,in, and These are preset weighting coefficients; Subsequently, the PID algorithm for optimizing deceleration was developed based on decreasing inertia weights. Formula for determining Trail Blazers position updates: ,in, for In the nth iteration round, the 1st The updated positions of the Trail Blazers For the current iteration round, These are normally distributed random numbers with a mean of 0 and a variance of 1. A random number between [0,1] is used to randomly select the update method, balancing exploration and convergence. These are random numbers that follow a normal distribution. Therefore, the positions of the first trailblazers are updated based on the trailblazer position update formula, resulting in the updated first trailblazers. Simultaneously, the Ikaruga optimized deceleration PID algorithm determines the decreasing inertia weights corresponding to the current iteration round. : ; And determine the decreasing inertia weights corresponding to the current iteration round. for: ; Therefore, based on decreasing inertia weights and decreasing inertia weight Update each First Watcher to obtain the updated First Watcher: ;in, In the nth iteration round, the 1st The updated location of the Watcher , , , All are preset weighting coefficients. For the current Overwatch's adaptability, The fitness of the current globally optimal position; Meanwhile, the dove-optimized deceleration PID algorithm updates the first joiner based on the perturbed global optimal and global worst positions, resulting in the updated first joiner as follows: ,in, This represents the globally optimal position occupied by the Trail Blazers in iteration t+1. It is a matrix of size 1×s. It is a 1×s matrix whose internal elements are all 1s. This means that each element in the matrix is ​​randomly assigned the value 1 or -1. ; Next, the Dove-Optimized Deceleration PID Algorithm determines the updated first update fitness of each first trailblazer, first joiner, and first watcher, and thus determines the updated global optimum position based on each first update fitness. Simultaneously, the Dove-Optimized Deceleration PID Algorithm determines the current iteration round. Finally, the Dove-Optimized Deceleration PID Algorithm determines the preset maximum iteration round and compares the current deceleration iteration round with the maximum iteration round. If the Dove-Optimized Deceleration PID Algorithm detects that the current deceleration iteration round has reached the maximum iteration round, it determines the global optimum position within the current iteration round as the target deceleration PID parameter. .

[0059] In this way, the electronic equipment can dynamically optimize the deceleration PID parameters based on the Ikaruga optimization algorithm and deceleration deviation to obtain the optimal deceleration PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal deceleration PID parameters, which significantly improves the control accuracy of the braking system.

[0060] Step S30: Obtain the actual hydraulic pressure of the vehicle and determine the hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure; Step S40: Determine the target second control parameter set based on the hydraulic pressure deviation, and determine the motor demand current in combination with the target second control parameter set, and control the vehicle's braking system according to the motor demand current; It should be noted that this actual hydraulic pressure is the real-time hydraulic pressure value monitored in the brake master cylinder or wheel cylinders of the EHB system within the vehicle. Furthermore, this second set of control parameters comprises the optimal hydraulic pressure PID parameters obtained through optimization for hydraulic pressure control, including proportional parameters. Differential parameters Integral parameters It is understandable that the second set of control parameters for this target can precisely adjust the hydraulic pressure deviation.

[0061] In this embodiment, after obtaining the target hydraulic pressure, the electronic device further detects the braking system to determine the actual hydraulic pressure generated on the braking system. The actual and target hydraulic pressures are then input to its configured hydraulic pressure PID controller. The hydraulic pressure PID controller calculates the hydraulic pressure deviation between the target and actual hydraulic pressures. Finally, the hydraulic pressure PID controller activates the preset dove-optimized hydraulic pressure PID algorithm. This algorithm selects a target second control parameter group that matches the hydraulic pressure deviation from a set of preset initial second control parameter groups. The algorithm then processes the target second control parameter group and the hydraulic pressure deviation using a preset PID calculation formula to obtain the motor current requirement that reduces the hydraulic pressure deviation. The hydraulic pressure PID controller uploads the motor current requirement to the electronic device. At this point, the electronic device generates a motor control command based on the motor current requirement to control the braking system. The electronic device then controls the braking system according to this command, ensuring accurate hydraulic pressure and deceleration, allowing the vehicle to complete the deceleration operation with precise hydraulic pressure and deceleration.

[0062] For example, such as Figure 2 As shown, after obtaining the target hydraulic pressure, the ECU accesses the pressure sensor configured within the EHB system to collect the actual hydraulic pressure generated by the wheel cylinders within the EHB system. The ECU compares the actual hydraulic pressure with the target hydraulic pressure to determine the hydraulic pressure deviation between the two. The ECU inputs the hydraulic pressure deviation to its configured hydraulic pressure PID controller. At this point, the hydraulic pressure PID controller performs differentiation processing on the hydraulic pressure deviation to obtain the hydraulic pressure deviation derivative. Finally, the hydraulic pressure PID controller starts the preset dove-optimized hydraulic pressure PID algorithm to iteratively optimize the initial hydraulic pressure PID parameters within the population. Based on the hydraulic pressure deviation and the hydraulic pressure deviation derivative, the fitness of each hydraulic pressure PID parameter after iterative optimization is determined, and then the target hydraulic pressure PID parameter that best matches the hydraulic pressure deviation derivative is output. The optimized hydraulic pressure PID algorithm then uses a preset PID calculation formula to adjust the target hydraulic pressure PID parameters. The hydraulic pressure is processed to obtain the required motor current that reduces hydraulic pressure deviation. The hydraulic pressure PID controller uploads the required motor current to the ECU. At this time, the ECU generates motor control commands for controlling the braking system of the EHB system based on the required motor current, and controls the braking system according to the motor control commands, thereby ensuring the accuracy of hydraulic pressure and deceleration, so that the vehicle can complete the deceleration operation according to accurate hydraulic pressure and deceleration. In this way, the electronic equipment can dynamically optimize the hydraulic pressure PID parameters based on the Izayoi optimization algorithm and hydraulic pressure deviation to obtain the optimal hydraulic pressure PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal hydraulic pressure PID parameters, which significantly improves the control accuracy of the braking system.

[0063] In one feasible implementation, the step of "determining the target second control parameter group based on the target liquid pressure and the actual liquid pressure" in step S40 above may specifically include steps S401 to S405: Step S401: Differentiate the hydraulic pressure deviation to obtain the hydraulic pressure deviation differential; Step S402: Determine multiple initial second control parameter groups, and determine the second initial fitness corresponding to each of the multiple initial second control parameter groups based on the hydraulic pressure deviation and the differential of the hydraulic pressure deviation; Step S403: Based on each of the second initial fitness, determine each second pioneer, each second joiner, and each second watchman in the plurality of initial second control parameter groups; Step S404: Determine the second global optimal position based on each of the second initial fitness values; Step S405: Combine the second global optimal position with the second second pioneer, the second second joiner and the second second watcher to obtain the target second control parameter group.

[0064] In this embodiment, after obtaining the hydraulic pressure deviation, the hydraulic pressure PID controller first performs differentiation on the hydraulic pressure deviation to obtain the hydraulic pressure deviation derivative. Then, the hydraulic pressure PID controller activates a preset dove-optimized hydraulic pressure PID algorithm. This algorithm determines multiple initial second control parameter sets for adjusting the hydraulic pressure deviation. Based on the hydraulic pressure deviation derivative, it determines the second initial fitness corresponding to each of the multiple initial second control parameter sets. Next, the dove-optimized hydraulic pressure PID algorithm sets a second pioneer, a second joiner, and a second watcher in the multiple initial second control parameter sets according to each second initial fitness. Finally, the dove-optimized hydraulic pressure PID algorithm determines the second... Finally, the Ikebana-optimized hydraulic pressure PID algorithm perturbs the second global optimal position to determine the second updated fitness corresponding to the perturbed second global optimal position. The Ikebana-optimized hydraulic pressure PID algorithm judges whether the perturbed second global optimal position is valid based on the second updated fitness. If the perturbed second global optimal position is determined to be valid, it iteratively optimizes each second pioneer, each second joiner, and each second watcher based on the perturbed second global optimal position. It then updates the perturbed second global optimal position based on the optimized second pioneer, each second joiner, and each second watcher until the number of iterations reaches the preset maximum number of iterations, and then outputs the target second control parameter set.

[0065] For example, after obtaining the hydraulic pressure deviation, the hydraulic pressure PID controller first collects the hydraulic pressure deviation within multiple detection cycles according to a preset detection cycle, and performs differential processing on the multiple hydraulic pressure deviations to obtain the hydraulic pressure deviation derivative. Then, the hydraulic pressure PID controller calls a preset dove-optimized hydraulic pressure PID algorithm to generate 100 sets of initial hydraulic pressure PID parameters within a preset parameter range based on a multidimensional uniform random generation strategy. The dove-optimized hydraulic pressure PID algorithm then uses the multiple initial hydraulic pressure PID parameters and the hydraulic pressure deviation derivative as inputs to a preset hydraulic pressure control simulation model to simulate a certain... The process of hydraulic pressure change over time is analyzed to obtain the second initial fitness corresponding to each of the 100 initial hydraulic pressure PID parameters. Then, the Dove-optimized hydraulic pressure PID algorithm selects the top 20% of the initial hydraulic pressure PID parameters based on their second initial fitness as pioneers, the remaining 80% as entrants, and randomly selects 20% of the pioneers and entrants as watchers. Finally, based on the ranking results, the Dove-optimized hydraulic pressure PID algorithm uses the hydraulic pressure PID parameter with the smallest second initial fitness as the second global optimum position. The dove-optimized hydraulic pressure PID algorithm acquires random variables between [0,1] based on the current iteration round. It compares the adaptive disturbance probability corresponding to the second global optimal position with the random variables. If the adaptive disturbance probability is greater than the random variables, it determines the disturbance term according to the preset first disturbance formula. The dove-optimized hydraulic pressure PID algorithm then optimizes the second global optimal position based on the disturbance term and the preset second disturbance formula to obtain the disturbed second global optimal position. The dove-optimized hydraulic pressure PID algorithm substitutes the disturbed second global optimal position into the hydraulic pressure control simulation model to determine the second update fitness of the disturbed second global optimal position. If the disturbed second global optimal position is determined to be valid based on the second update fitness, the dove-optimized hydraulic pressure PID algorithm updates each second pioneer, each second joiner, and each second watcher. Based on the updated second pioneers, second joiners, and second watchers, it optimizes the disturbed second global optimal position until the iteration round reaches the preset maximum iteration round. Finally, the determined second global optimal position is set as the target hydraulic pressure PID control parameter. .

[0066] In this way, the electronic equipment can dynamically optimize the hydraulic pressure PID parameters based on the Izayoi optimization algorithm and hydraulic pressure deviation to obtain the optimal hydraulic pressure PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal hydraulic pressure PID parameters, which significantly improves the control accuracy of the braking system.

[0067] In one feasible implementation, step S405 above may specifically include steps S4051 to S4056: Step S4051: Determine the randomly generated variable corresponding to the second global optimal position; Step S4052: When it is detected that the randomly generated variable has reached a preset adaptive threshold, the second global optimal position is perturbed, and the second update fitness of the perturbed second global optimal position is determined; Step S4053: If the second updated fitness is detected to be greater than the second initial fitness of the second global optimal position, obtain the preset decreasing inertia weight and determine the second global worst position; Step S4054: Update each of the second pioneers and each of the second watchers based on the preset decreasing inertia weights, and update each of the second joiners based on their respective second initial fitness, second global best position and second global worst position; Step S4055: Determine the updated second global optimal position based on the updated second pioneers, second joiners, and second watchers, and determine the current hydraulic pressure iteration round; Step S4056: If it is detected that the current hydraulic pressure iteration round has reached the preset maximum iteration round, the updated second global optimal position is determined as the target second control parameter group.

[0068] In this embodiment, after determining the second global optimum position, the Dove-Optimized Hydraulic Pressure PID algorithm first determines the random variable based on the current iteration round. Simultaneously, the algorithm determines the randomly generated variable corresponding to the second global optimum position. Then, the algorithm compares the adaptive perturbation probability corresponding to the second global optimum position with the random variable. If the adaptive perturbation probability is detected to be greater than the random variable, the algorithm performs perturbation optimization on the second global optimum position to obtain the perturbed second global optimum position. The algorithm then substitutes the perturbed second global optimum position into the hydraulic pressure control simulation model to determine the second updated fitness of the perturbed second global optimum position. Finally, the algorithm compares the second updated fitness with the second initial fitness of the second global optimum position. If the second updated fitness is detected to be greater than the second initial fitness, the algorithm determines that the perturbed second global optimum position is valid and obtains the desired fitness. With a preset decreasing inertia weight and a second global worst position, the Dove-Optimized Hydraulic Pressure PID algorithm updates each second pioneer and each second watcher based on the decreasing inertia weight. Simultaneously, the Dove-Optimized Hydraulic Pressure PID algorithm updates each second joiner based on their respective second initial fitness, the perturbed second global optimal position, and the second global worst position. Then, the Dove-Optimized Hydraulic Pressure PID algorithm determines the updated second updated fitness for each second pioneer, each second watcher, and each second joiner, thereby determining the updated second global optimal position based on each second fitness. Simultaneously, the Dove-Optimized Hydraulic Pressure PID algorithm determines the current deceleration iteration round. Finally, the Dove-Optimized Hydraulic Pressure PID algorithm obtains the preset maximum iteration round and compares the current hydraulic pressure iteration round with the maximum iteration round. Therefore, when the current hydraulic pressure iteration round reaches the maximum iteration round, the updated second global optimal position is determined as the target second control parameter set.

[0069] For example, the Dove-Optimized Liquid Pressure PID algorithm obtains a random variable between [0,1] based on the current iteration. Then, the Dove-Optimized Liquid Pressure PID algorithm compares the adaptive perturbation probability corresponding to the second global optimal position with the random variable. If the adaptive perturbation probability is detected to be greater than the random variable, a perturbation term is determined according to the aforementioned preset first perturbation formula. The Dove-Optimized Liquid Pressure PID algorithm then performs perturbation optimization on the second global optimal position based on the perturbation term and the aforementioned preset second perturbation formula to obtain the perturbed second global optimal position. The Dove-Optimized Liquid Pressure PID algorithm will... The perturbed second global optimum position is substituted into the hydraulic pressure control simulation model to determine the second updated fitness of the perturbed second global optimum position. Then, the dove-optimized hydraulic pressure PID algorithm compares the second updated fitness with the second initial fitness corresponding to each initial hydraulic pressure PID parameter. If the second updated fitness is detected to be greater than each second initial fitness, the perturbed second global optimum position is determined as the latest global optimum position. The worst global position is recorded based on the perturbed updated fitness. At this point, the dove-optimized hydraulic pressure PID algorithm obtains the decreasing inertia weight corresponding to the current iteration. The dove-optimized hydraulic pressure PID algorithm updates each second pioneer using the aforementioned pioneer position update formula based on decreasing inertia weights, obtaining the updated second pioneers. Simultaneously, the dove-optimized hydraulic pressure PID algorithm uses decreasing inertia weights... and decreasing inertia weight The algorithm updates each second watchman to obtain an updated second watchman. Simultaneously, the Dove-optimized hydraulic pressure PID algorithm updates the second joiner based on the perturbed global optimal and global worst positions to obtain an updated second joiner. Then, the Dove-optimized hydraulic pressure PID algorithm determines the second update fitness of each updated second pioneer, each second joiner, and each second watchman, thereby determining the updated global optimal position based on each second update fitness. Simultaneously, the Dove-optimized hydraulic pressure PID algorithm determines the current iteration round. Finally, the Dove-optimized hydraulic pressure PID algorithm determines the preset maximum iteration round and compares the current hydraulic pressure iteration round with the maximum iteration round. At this point, if the Dove-optimized deceleration PID algorithm detects that the current hydraulic pressure iteration round has reached the maximum iteration round, it determines the global optimal position within the current iteration round as the target hydraulic pressure PID parameter. .

[0070] In this way, the electronic equipment can dynamically optimize the hydraulic pressure PID parameters based on the Izayoi optimization algorithm and hydraulic pressure deviation to obtain the optimal hydraulic pressure PID parameters without the need for technicians to calibrate the PID parameters based on experience. Then, it can accurately control the braking system according to the optimal hydraulic pressure PID parameters, which significantly improves the control accuracy of the braking system.

[0071] Furthermore, in this embodiment and another embodiment, after controlling the braking system, the electronic device can also collect the maximum and minimum deviation thresholds of deceleration and hydraulic pressure generated by the vehicle under different road conditions such as uniform low-friction road, uniform high-friction road, split road, docking road, and checkerboard road. Then, based on the maximum and minimum deviation thresholds and the constructed optimal deceleration PID parameters and optimal hydraulic pressure PID parameters, a PID lookup table is constructed so that the vehicle can quickly determine the optimal PID parameters that match the current road conditions, current deceleration deviation, and current hydraulic pressure deviation by querying the PID lookup table.

[0072] In this embodiment, when the driver depresses the brake pedal to reduce the vehicle's speed, the electronic device first determines the target deceleration required by the driver based on the change in the brake pedal angle. Simultaneously, the electronic device uses the vehicle's inertial measurement unit to collect longitudinal acceleration data of the vehicle body. Based on this data, it determines the actual deceleration of the vehicle during the deceleration process. The electronic device then inputs the actual and target decelerations into its configured deceleration PID controller. The deceleration PID controller calculates the deceleration deviation between the target and actual decelerations. Next, the deceleration PID controller activates a preset "Dove-optimized deceleration PID algorithm." This algorithm selects a target first control parameter group that matches the deceleration deviation from preset initial first control parameter groups. The target first control parameter group and the deceleration deviation are then processed using a preset PID calculation formula to obtain a target hydraulic pressure that reduces the deceleration deviation. Finally, after obtaining the target hydraulic pressure, the electronic device... The braking system is tested to determine the actual hydraulic pressure generated on it. The actual and target hydraulic pressures are then input into a configured hydraulic pressure PID controller. The PID controller calculates the hydraulic pressure deviation between the target and actual hydraulic pressures. Finally, the PID controller activates a preset "Dove-Optimized Hydraulic Pressure PID Algorithm." This algorithm selects a target second control parameter set that matches the hydraulic pressure deviation from a set of preset initial second control parameter sets. The algorithm then processes the target second control parameter set and the hydraulic pressure deviation using a preset PID calculation formula to obtain the motor current requirement that reduces the hydraulic pressure deviation. The PID controller uploads this motor current requirement to the electronic equipment. The electronic equipment then generates motor control commands based on these commands to control the braking system, ensuring accurate hydraulic pressure and deceleration, allowing the vehicle to decelerate according to precise hydraulic pressure and deceleration.

[0073] Thus, this application solves the technical problem of reduced control accuracy of braking systems in related technologies. Specifically, this application uses a biomimetic dove algorithm to screen the first target control parameter for reducing deceleration deviation, and uses the biomimetic dove algorithm to screen and process the first target control parameter and hydraulic pressure deviation to determine the second target control parameter for reducing hydraulic pressure deviation. Based on the second target control parameter, the motor demand current for controlling the braking system is determined. This method can automatically screen deceleration PID parameters and hydraulic pressure PID parameters that match the current road conditions based on deceleration deviation and hydraulic pressure deviation without requiring technicians to calibrate PID parameters based on experience. Then, the braking system can be accurately controlled according to the deceleration PID parameters and hydraulic pressure PID parameters, significantly improving the control accuracy of the braking system.

[0074] This application also provides a control device for a braking system; please refer to [reference needed]. Figure 4 The control device for the braking system includes: The deceleration detection module 10 is used to acquire the target deceleration and the actual deceleration of the vehicle, and to determine the deceleration deviation between the target deceleration and the actual deceleration; The first PID screening module 20 is used to determine the target first control parameter set based on the deceleration deviation, and to determine the target hydraulic pressure in combination with the target first control parameter set; The hydraulic pressure detection module 30 acquires the actual hydraulic pressure of the vehicle and determines the hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure. The second PID screening module 40 determines the target second control parameter group based on the hydraulic pressure deviation, and determines the motor demand current in combination with the target second control parameter group, and controls the vehicle's braking system according to the motor demand current.

[0075] In one feasible implementation, the first PID screening module 20 described above is further configured to: The differential of the deceleration deviation is obtained by performing differential processing on the deceleration deviation. Multiple initial first control parameter sets are determined, and a first initial fitness corresponding to each of the multiple initial first control parameter sets is determined based on the differential of the deceleration deviation and the deceleration deviation; Based on each of the first initial fitness values, the multiple initial first control parameter sets are iterated to obtain the target first control parameter set.

[0076] In one feasible implementation, the first PID screening module 20 described above is further configured to: Determine the preset search area and preset population size; Based on the preset population size, multiple initial first control parameter sets are determined within the preset search range.

[0077] In one feasible implementation, the first PID screening module 20 described above is further configured to: Based on each of the first initial fitness, each first pioneer, each first joiner, and each first watcher are determined from multiple sets of the first initial control parameters; The first global optimal position is determined based on each of the first initial fitness values; The first global optimum position is perturbed, and the first update fitness of the perturbed first global optimum position is determined. The target first control parameter set is obtained by iterating over each of the first pioneers, each of the first joiners and each of the first watchers in combination with the first updated fitness.

[0078] In one feasible implementation, the first PID screening module 20 described above is further configured to: If the first updated fitness is detected to be greater than the first initial fitness of the first global optimal position, a preset decreasing inertial weight is obtained and the first global worst position is determined. The first pioneers and the first watchers are updated based on the decreasing inertia weights, and the first joiners are updated based on their respective first initial fitness, first global best position, and first global worst position. Based on the updated positions of each first trailblazer, first joiner, and first watcher, determine the updated first global optimal position and the current deceleration iteration round. If the current deceleration iteration round is detected to have reached the preset maximum iteration round, the updated first global optimal position is determined as the target first control parameter group.

[0079] In one feasible implementation, the second PID filtering module 40 described above is further used for: The differential of the hydraulic pressure deviation is obtained by performing differential processing on the hydraulic pressure deviation. Multiple initial second control parameter sets are determined, and the second initial fitness corresponding to each of the multiple initial second control parameter sets is determined based on the hydraulic pressure deviation and the derivative of the hydraulic pressure deviation; Each second pioneer, each second joiner, and each second watchman are determined from among the multiple sets of said initial second control parameters based on each of the second initial fitness; The second global optimal position is determined based on each of the second initial fitness values; The target second control parameter set is obtained by iteratively processing each second pioneer, each second joiner, and each second watcher based on the second global optimal position.

[0080] In one feasible implementation, the second PID filtering module 40 described above is further used for: Determine the randomly generated variable corresponding to the second global optimal position; If the randomly generated variable is detected to have reached a preset adaptive threshold, the second global optimal position is perturbed, and the second update fitness of the perturbed second global optimal position is determined. If the second updated fitness is detected to be greater than the second initial fitness of the second global optimal position, a preset decreasing inertial weight is obtained and the second global worst position is determined; The second pioneers and the second watchers are updated based on the preset decreasing inertia weights, and the second joiners are updated based on their respective second initial fitness, second global best position and second global worst position. Based on the updated second pioneers, second joiners, and second watchers, determine the updated second global optimal position and the current hydraulic pressure iteration round; If the current hydraulic pressure iteration round is detected to have reached the preset maximum iteration round, the updated second global optimal position is determined as the target second control parameter group.

[0081] The braking system control device provided in this application, employing the braking system control method in the above embodiments, can solve the technical problem of reduced control accuracy of braking systems in related technologies. Compared with the prior art, the beneficial effects of the braking system control device provided in this application are the same as those of the braking system control method provided in the above embodiments, and other technical features in the braking system control device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0082] This application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the control method of the braking system in Embodiment 1 above.

[0083] The following is for reference. Figure 5 The diagram illustrates a structural schematic of an electronic device suitable for implementing the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, an electronic device with an internally configured deceleration PID controller or hydraulic pressure PID controller, capable of connecting to the EHB system configured in the vehicle, as the execution entity. It is understood that this electronic device may specifically be an ECU within the vehicle. Figure 5The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0084] like Figure 5 As shown, the electronic device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the electronic device. The processing unit 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. The communication device 1009 allows the electronic device to communicate wirelessly or wiredly with other devices to exchange data. Although the diagrams show electronic devices with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented alternatively.

[0085] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0086] The electronic device provided in this application, employing the control method of the braking system in the above embodiments, can solve the technical problem of reduced control accuracy of the braking system in related technologies. Compared with the prior art, the beneficial effects of the electronic device provided in this application are the same as those of the control method of the braking system provided in the above embodiments, and other technical features of the electronic device are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0087] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0089] This application also provides a vehicle including the electronic equipment described above, wherein when the vehicle is executed, it implements the steps of the control method for the braking system described above.

[0090] The vehicle provided in this application can solve the technical problem of reduced control accuracy of the braking system in related technologies. Compared with the prior art, the beneficial effects of the vehicle provided in this application are the same as the beneficial effects of the braking system control method provided in the above embodiments, and will not be repeated here.

[0091] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the control method of the braking system in the above embodiments.

[0092] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0093] The aforementioned computer-readable storage medium may be included in an electronic device or may exist independently without being assembled into an electronic device.

[0094] The aforementioned computer-readable storage medium carries one or more programs that, when executed by an electronic device, cause the electronic device to: acquire a target deceleration and an actual deceleration of the vehicle, and determine a deceleration deviation between the target deceleration and the actual deceleration; determine a first set of target control parameters based on the deceleration deviation, and determine a target hydraulic pressure in conjunction with the first set of target control parameters; acquire the actual hydraulic pressure of the vehicle, and determine a hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure; determine a second set of target control parameters based on the hydraulic pressure deviation, and determine a motor demand current in conjunction with the second set of target control parameters, and control the braking system of the vehicle according to the motor demand current.

[0095] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0096] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0097] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0098] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the control method of the above-described braking system, which can solve the technical problem of reduced control accuracy of the braking system in related technologies. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the control method of the braking system provided in the above embodiments, and will not be repeated here.

[0099] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the control method for the braking system as described above.

[0100] The computer program product provided in this application can solve the technical problem of reduced control accuracy of braking systems in related technologies. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the braking system control method provided in the above embodiments, and will not be repeated here.

[0101] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A control method for a braking system, characterized in that, The control method for the braking system includes: Obtain the target deceleration and actual deceleration of the vehicle, and determine the deceleration deviation between the target deceleration and the actual deceleration; The first set of target control parameters is determined based on the deceleration deviation, and the target hydraulic pressure is determined in combination with the first set of target control parameters. The actual hydraulic pressure of the vehicle is obtained, and the hydraulic pressure deviation between the target hydraulic pressure and the actual hydraulic pressure is determined. The target second control parameter set is determined based on the hydraulic pressure deviation, and the motor demand current is determined in combination with the target second control parameter set. The braking system of the vehicle is then controlled according to the motor demand current.

2. The control method for the braking system as described in claim 1, characterized in that, The step of determining the first set of target control parameters based on the deceleration deviation includes: The differential of the deceleration deviation is obtained by performing differential processing on the deceleration deviation. Multiple initial first control parameter sets are determined, and a first initial fitness corresponding to each of the multiple initial first control parameter sets is determined based on the differential of the deceleration deviation and the deceleration deviation; Based on each of the first initial fitness values, the multiple initial first control parameter sets are iterated to obtain the target first control parameter set.

3. The control method for the braking system as described in claim 2, characterized in that, The step of determining multiple initial first control parameter groups includes: Determine the preset search area and preset population size; Based on the preset population size, multiple initial first control parameter sets are determined within the preset search range.

4. The control method for the braking system as described in claim 2, characterized in that, The step of iterating through multiple initial first control parameter sets based on each of the first initial fitness values ​​to obtain a target first control parameter set includes: Based on each of the first initial fitness, each first pioneer, each first joiner, and each first watcher are determined from multiple sets of the first initial control parameters; The first global optimal position is determined based on each of the first initial fitness values; The first global optimum position is perturbed, and the first update fitness of the perturbed first global optimum position is determined. The target first control parameter set is obtained by iterating over each of the first pioneers, each of the first joiners and each of the first watchers in combination with the first updated fitness.

5. The control method for the braking system as described in claim 4, characterized in that, The step of iterating through each of the first pioneers, each of the first joiners, and each of the first watchers using the first updated fitness to obtain the target first control parameter set includes: If the first updated fitness is detected to be greater than the first initial fitness of the first global optimal position, a preset decreasing inertial weight is obtained and the first global worst position is determined. The first pioneers and the first watchers are updated based on the decreasing inertia weights, and the first joiners are updated based on their respective first initial fitness, first global best position, and first global worst position. Based on the updated positions of each first trailblazer, first joiner, and first watcher, determine the updated first global optimal position and the current deceleration iteration round. If the current deceleration iteration round is detected to have reached the preset maximum iteration round, the updated first global optimal position is determined as the target first control parameter group.

6. The control method for the braking system as described in claim 1, characterized in that, The step of determining the target second control parameter set based on the hydraulic pressure deviation includes: The differential of the hydraulic pressure deviation is obtained by performing differential processing on the hydraulic pressure deviation. Multiple initial second control parameter sets are determined, and the second initial fitness corresponding to each of the multiple initial second control parameter sets is determined based on the hydraulic pressure deviation and the derivative of the hydraulic pressure deviation; Each second pioneer, each second joiner, and each second watchman are determined from among the multiple sets of said initial second control parameters based on each of the second initial fitness; The second global optimal position is determined based on each of the second initial fitness values; The target second control parameter set is obtained by iteratively processing each second pioneer, each second joiner, and each second watcher based on the second global optimal position.

7. The control method for the braking system as described in claim 6, characterized in that, The step of iteratively processing each of the second pioneers, each of the second joiners, and each of the second watchmen based on the second global optimal position to obtain the target second control parameter set includes: Determine the randomly generated variable corresponding to the second global optimal position; If the randomly generated variable is detected to have reached a preset adaptive threshold, the second global optimal position is perturbed, and the second update fitness of the perturbed second global optimal position is determined. If the second updated fitness is detected to be greater than the second initial fitness of the second global optimal position, a preset decreasing inertial weight is obtained and the second global worst position is determined; The second pioneers and the second watchers are updated based on the preset decreasing inertia weights, and the second joiners are updated based on their respective second initial fitness, second global best position and second global worst position. Based on the updated second pioneers, second joiners, and second watchers, determine the updated second global optimal position and the current hydraulic pressure iteration round; If the current hydraulic pressure iteration round is detected to have reached the preset maximum iteration round, the updated second global optimal position is determined as the target second control parameter group.

8. An electronic device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the control method for the braking system as described in any one of claims 1 to 7.

9. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 8.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the control method of the braking system as described in any one of claims 1 to 7.

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