Composite braking method, system and vehicle for wheel hub motor driven vehicle

Abstract

The present application discloses a compound braking method, system and vehicle for a vehicle driven by a hub motor. The method effectively determines whether the vehicle has a locking tendency by obtaining the slip rate of each wheel of the vehicle, the power generation efficiency MAP diagram of the hub motor and the charging efficiency MAP diagram of the battery. Therefore, when the vehicle does not have a locking tendency, the vehicle's energy recovery efficiency is maximized by optimizing the distribution of the vehicle's driving force. When the vehicle has a locking tendency, the vehicle is subjected to anti-lock control by a fuzzy adaptive PID compound anti-lock control algorithm to achieve safe control of the vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle braking control, and in particular to a composite braking method, system and vehicle for a vehicle driven by a hub motor. Background Art

[0002] At present, new energy vehicles are the inevitable direction of future development of the automobile industry. However, they are limited by power battery technology and cannot meet the needs of long-distance travel. Therefore, the solution of making full use of regenerative braking technology to improve the cruising range of new energy vehicles has received widespread attention.

[0003] However, existing brake energy recovery systems have complex adjustment parameters and poor real-time performance, resulting in long system response times and low energy utilization, making them difficult to implement on actual vehicles. Furthermore, due to the risk of vehicle slippage during operation, it is difficult to ensure vehicle safety during the operation of the brake energy recovery system.

[0004] Therefore, in the process of braking control of a vehicle, the prior art has the problems of low energy utilization and low safety factor. Summary of the Invention

[0005] In view of this, it is necessary to provide a composite braking method, system and vehicle for a vehicle driven by a hub motor, so as to solve the problems of low energy utilization and low safety factor in the prior art.

[0006] In order to solve the above problems, the present invention provides a compound braking method for a vehicle driven by an in-wheel motor, comprising:

[0007] Obtain the slip rate of each wheel of the vehicle, the power generation efficiency MAP of the hub motor, and the charging efficiency MAP of the battery;

[0008] When the slip rate of each wheel does not exceed the slip rate threshold, the vehicle is regenerated based on the PSO according to the power generation efficiency MAP and the charging efficiency MAP.

[0009] When the slip rate of any wheel exceeds the slip rate threshold, the vehicle is controlled by the composite anti-lock braking control algorithm based on fuzzy adaptive PID.

[0010] Furthermore, according to the power generation efficiency MAP and the charging efficiency MAP, the vehicle is subjected to energy recovery based on the PSO, including:

[0011] Construct a parallel compound braking system model for a vehicle;

[0012] Determine the vehicle's energy recovery efficiency optimization target based on the power generation efficiency MAP and charging efficiency MAP;

[0013] According to the energy recovery efficiency optimization target and the slip rate of each wheel, the vehicle energy recovery is performed based on PSO.

[0014] Furthermore, according to the energy recovery efficiency optimization target and the slip rate of each wheel, the vehicle is subjected to energy recovery based on PSO, including:

[0015] Determine the control variables based on the power generation efficiency MAP diagram and the charging efficiency MAP diagram;

[0016] Determine the objective function and constraints based on the energy recovery efficiency optimization goal;

[0017] According to the slip rate of each wheel and the objective function, the vehicle energy is recovered based on PSO.

[0018] Furthermore, the constraints include the maximum allowable charging power limit of the battery, the required braking torque of the vehicle, ECE regulatory restrictions, and the braking characteristic restrictions of the hub motor.

[0019] Furthermore, a composite anti-lock braking control algorithm based on fuzzy adaptive PID is used to control the vehicle's anti-lock braking, including:

[0020] Determine the optimal slip rate based on the slip rate and road adhesion conditions;

[0021] According to the optimal slip ratio, a well-tuned fuzzy controller is determined;

[0022] The vehicle's anti-lock braking system is controlled based on a well-tuned fuzzy controller.

[0023] Furthermore, based on the optimal slip ratio, a well-tuned fuzzy controller is determined, including:

[0024] According to the optimal slip ratio, the PID parameters are adjusted by trial and error to determine the fully adjusted fuzzy controller.

[0025] Furthermore, the slip rate of each wheel of the vehicle is obtained, including:

[0026] Get the wheel speed of the vehicle;

[0027] The slip rate of each wheel is determined based on the wheel speed of each wheel and the reference vehicle speed.

[0028] Furthermore, the wheel speed of each vehicle is obtained, including:

[0029] The wheel speed of each vehicle is estimated and determined based on the Federated Kalman Filter.

[0030] In order to solve the above problems, the present invention further provides a composite braking system for a vehicle driven by an in-wheel motor, comprising:

[0031] The slip rate acquisition module is used to obtain the slip rate of each wheel of the vehicle, the power generation efficiency MAP of the hub motor and the charging efficiency MAP of the battery;

[0032] An energy recovery module, configured to recover vehicle energy based on the PSO according to a power generation efficiency MAP and a charging efficiency MAP when the slip rate of each wheel does not exceed a slip rate threshold;

[0033] The braking safety guarantee module is used to perform anti-lock control on the vehicle based on a fuzzy adaptive PID composite anti-lock control algorithm when the slip rate of any wheel exceeds the slip rate threshold.

[0034] In order to solve the above problems, the present invention further provides a vehicle, comprising the composite braking system of the vehicle driven by the in-wheel motor as described above.

[0035] The beneficial effects of adopting the above technical solution are as follows: the present invention provides a compound braking method, system and vehicle for a vehicle driven by a hub motor. The method effectively determines whether the vehicle has a locking tendency by obtaining the slip rate of each wheel of the vehicle, the power generation efficiency MAP diagram of the hub motor and the charging efficiency MAP diagram of the battery. Therefore, when the vehicle does not have a locking tendency, the vehicle's energy recovery efficiency is maximized by optimizing the distribution of the vehicle's driving force; when the vehicle has a locking tendency, the vehicle is subjected to anti-lock control by a fuzzy adaptive PID compound anti-lock control algorithm to achieve vehicle safety control. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic flow chart of an embodiment of a compound braking method for a vehicle driven by an in-wheel motor provided by the present invention;

[0037] Figure 2 A schematic diagram of a process for recovering energy from a vehicle according to an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of a flow chart of an embodiment of determining a vehicle energy recovery function provided by the present invention;

[0039] Figure 4 A schematic diagram of a flow chart of an embodiment of anti-lock braking control for a vehicle provided by the present invention;

[0040] Figure 5 This is a structural schematic diagram of an embodiment of a compound braking system for a vehicle driven by an in-wheel motor provided by the present invention. DETAILED DESCRIPTION

[0041] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, and are not used to limit the scope of the present invention.

[0042] Before describing the embodiment, the following sections will first describe the hub motor's power generation efficiency MAP, battery charging efficiency MAP, PSO, fuzzy adaptive PID, Simulink, and braking strength:

[0043] The power generation efficiency MAP diagram of the hub motor refers to an image that is specifically expressed using a coordinate graph after determining the inherent properties of the hub motor and, based on the relationship between its various parameters, using simulation technology to determine the quantitative relationship between the speed, torque and motor efficiency of the hub motor.

[0044] The battery charging efficiency MAP diagram refers to an image that uses a coordinate graph to represent the quantitative relationship between the battery's state of charge (SOC) and real-time charging power by performing data statistics on the battery's state of charge (SOC) and real-time charging power.

[0045] Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique that mimics the swarming behavior of insects, animal flocks, bird flocks, and fish schools. These groups search for food in a cooperative manner, and each member of the group continuously changes its search pattern by learning from its own experience and the experience of other members.

[0046] Fuzzy adaptive PID is based on the PID algorithm. It takes the error e and the error change rate ec as input, uses fuzzy rules for fuzzy reasoning, and queries the fuzzy matrix table to adjust parameters to meet the requirements of e and ec for PID parameter self-tuning at different times.

[0047] Simulink is a block diagram environment for multidomain simulation and model-based design. It supports system design, simulation, automatic code generation, and continuous testing and verification of embedded systems. Simulink provides a graphical editor, a customizable block library, and solvers for modeling and simulating dynamic systems.

[0048] Braking strength is the braking capacity of the braking system. Braking strength is the ratio of the maximum braking deceleration without locking the wheel to the adhesion coefficient between the wheel and the road. It is also the ratio of the braking strength when the wheel is about to lock to the utilized adhesion coefficient.

[0049] Currently, regenerative braking technology is primarily used to increase the range of new energy vehicles. However, existing brake energy recovery systems, due to complex adjustment parameters, result in low braking and energy recovery efficiency. Furthermore, it is difficult to strictly ensure vehicle safety during braking control.

[0050] Therefore, in the process of braking control of a vehicle, the prior art has the problems of low energy utilization and low safety factor.

[0051] In order to solve the above problems, the present invention provides a composite braking method, system and vehicle for a vehicle driven by an in-wheel motor, which are described in detail below.

[0052] like Figure 1 As shown, Figure 1 A schematic flow chart of an embodiment of a composite braking method for a vehicle driven by an in-wheel motor provided by the present invention includes:

[0053] Step S101: Obtain the slip ratio of each wheel of the vehicle, the power generation efficiency MAP of the hub motor, and the charging efficiency MAP of the battery.

[0054] Step S102: When the slip rate of each wheel does not exceed the slip rate threshold, energy recovery is performed on the vehicle based on the PSO according to the power generation efficiency MAP map and the charging efficiency MAP map.

[0055] Step S103: When the slip rate of any wheel exceeds the slip rate threshold, anti-lock control is performed on the vehicle based on the fuzzy adaptive PID composite anti-lock control algorithm.

[0056] In this embodiment, first, the relationship between the slip rate of each wheel and the slip rate threshold is used to determine whether the vehicle has a locking tendency. Then, if the slip rate of each wheel does not exceed the slip rate threshold, that is, if the vehicle has no locking tendency, the braking torque is distributed to each wheel based on the PSO according to the power generation efficiency MAP and the charging efficiency MAP to maximize the vehicle's energy recovery efficiency. Finally, if the slip rate of any wheel exceeds the slip rate threshold, that is, if the vehicle has a locking tendency, the vehicle is controlled using the fuzzy adaptive PID composite anti-lock control algorithm to ensure vehicle braking safety.

[0057] It can be understood that in this embodiment, by monitoring the slip rate of each wheel, it is possible to effectively determine whether the vehicle is prone to locking. This allows the vehicle's energy recovery efficiency to be maximized when the vehicle is not prone to locking. When the vehicle is prone to locking, the primary goal is to ensure vehicle braking safety. In summary, this embodiment maximizes the vehicle's energy recovery efficiency while ensuring safe vehicle operation.

[0058] It should be noted that PSO adopts the existing conventional particle swarm optimization algorithm, and its principle and process are not described here.

[0059] In a specific embodiment, the slip rate of each wheel of the vehicle driven by the hub motor is calculated in real time, and 20% is used as a slip rate threshold to judge the vehicle braking state. If the threshold is exceeded, it is determined that the wheel has a locking tendency.

[0060] As a preferred embodiment, in step S101, in order to calculate the slip rate of each wheel of the current vehicle, first, the wheel speed of the vehicle is obtained; then, the slip rate of each wheel is determined by calculation based on the wheel speed of each wheel and the reference vehicle speed.

[0061] Furthermore, in order to obtain the wheel speed of each wheel of the vehicle, the wheel speed of each wheel of the vehicle is estimated and determined according to the Federated Kalman Filter.

[0062] In a specific embodiment, a filter is designed based on the Federated Kalman Theory to estimate the longitudinal vehicle speed. During vehicle braking, the wheel speeds of each wheel obtained through the hub motor resolver signal and the reference vehicle speed can be used to calculate the current slip rate of each wheel of the vehicle.

[0063] In order to obtain the power generation efficiency MAP diagram of the hub motor, data analysis is performed on the selected hub motor, and the power generation efficiency MAP diagram of the hub motor can also be determined by searching literature.

[0064] In order to determine the battery charging efficiency MAP diagram, combined with the parameters of the lithium iron phosphate battery, the relationship between the battery charging efficiency and the battery's current state of charge SOC and real-time charging power without considering the influence of the battery temperature is analyzed, thereby determining the battery charging efficiency MAP diagram.

[0065] As a preferred embodiment, in step S102, when the slip rate of each wheel does not exceed the slip rate threshold, in order to recover energy for the vehicle, Figure 2 As shown, Figure 2 A schematic diagram of a process for recovering energy from a vehicle according to an embodiment of the present invention includes:

[0066] Step S121: Constructing a parallel compound braking system model of the vehicle.

[0067] Step S122: Determine the energy recovery efficiency optimization target of the vehicle based on the power generation efficiency MAP and the charging efficiency MAP.

[0068] Step S123: Perform energy recovery on the vehicle based on the PSO according to the energy recovery efficiency optimization target and the slip rate of each wheel.

[0069] In this embodiment, first, it is necessary to construct a parallel compound braking system model of the vehicle, that is, it is necessary to model the vehicle to facilitate data analysis; next, based on the power generation efficiency MAP diagram and the charging efficiency MAP diagram, the vehicle's energy recovery efficiency optimization target is determined, that is, it is necessary to set an indicator that can ultimately represent the energy recovery efficiency; finally, based on the energy recovery efficiency optimization target and the slip rate of each wheel, the vehicle's energy recovery is performed based on PSO.

[0070] In this embodiment, a parallel compound braking system model of the vehicle is constructed to accurately obtain the energy recovery efficiency. Based on the energy recovery efficiency optimization target, the driving force is distributed to each wheel in combination with the slip rate of each wheel. Continuous iterative optimization is performed based on the PSO technology to ultimately maximize the energy recovery efficiency.

[0071] As a preferred embodiment, in step S121, in order to construct a parallel compound braking system model of a vehicle, firstly, a parallel compound braking system model is constructed on Simulink according to the braking system structure diagram and motor performance of an actual vehicle.

[0072] In a specific embodiment, based on the dynamic analysis of the vehicle, the dynamic equation is obtained as follows:

[0073]

[0074] Among them, F x It is the resultant force of the tangential reaction force of the ground acting on the front and rear wheels; M 1 / 2 Is 1 / 2 of the vehicle mass; F wz It is the combined force of the front and rear wheel rolling resistance, air resistance and slope resistance; F z1 、F z2 are the normal forces acting on the front and rear wheels respectively; F hc is the slope resistance; b1 , ψ b2 They are the braking force coefficients related to the adhesion state of the front and rear wheels to the ground.

[0075] As a preferred embodiment, in step S122, in order to determine the energy recovery efficiency optimization target of the vehicle, it is necessary to first determine the influencing factors of the energy recovery efficiency and determine the relationship between them.

[0076] In a specific embodiment, the factors affecting the regenerative braking energy recovery efficiency are analyzed based on the wheel hub motor power generation efficiency MAP diagram and the power battery charging efficiency MAP diagram. On the one hand, the power generation efficiency expression is obtained as follows:

[0077] μ m =F m (n, T)

[0078] Among them, μm is the power generation efficiency of the hub motor; n is the speed of the hub motor; T is the output torque of the hub motor, that is, the electric braking torque.

[0079] On the other hand, the charging efficiency is expressed as:

[0080] μ b =f b (SOC, P b )

[0081] Among them, f b Indicates battery state of charge SOC and charging power P b Mathematical relationship between volts and battery charging efficiency.

[0082] As a preferred embodiment, in step S123, in order to specifically describe the function determination process for energy recovery of the vehicle, as shown in FIG. Figure 3 As shown, Figure 3 A schematic diagram of a flow chart of an embodiment of determining a vehicle energy recovery function provided by the present invention includes:

[0083] Step S1231: Determine control variables based on the power generation efficiency MAP map and the charging efficiency MAP map.

[0084] Step S1232: Determine the objective function and constraint conditions according to the energy recovery efficiency optimization target.

[0085] Step S1233: Perform energy recovery on the vehicle based on the PSO according to the slip rate of each wheel and the objective function.

[0086] In this embodiment, first, the control variables are determined based on the power generation efficiency MAP diagram and the charging efficiency MAP diagram, that is, all relevant variables in the power generation efficiency MAP diagram and the charging efficiency MAP diagram are used as control variables to determine the influencing factors of the regenerative braking energy recovery efficiency; then, based on the energy recovery efficiency optimization goal, the objective function and constraints are determined, that is, the target value and constraints that ultimately need to be optimized for the vehicle energy recovery function are determined; finally, based on the slip rate of each wheel and the objective function, continuous iterative optimization is performed based on PSO to obtain the maximum value of the energy recovery efficiency optimization target, thereby realizing energy recovery for the vehicle.

[0087] In one embodiment, the total energy recovery efficiency of the vehicle is controlled by distributing the electric braking force between the front and rear wheels. Therefore, the control variables are selected as:

[0088] X = [X1, X2] T =[T regf , T regr ] T

[0089] Among them, Tregf 、T regr The electric braking torque of the front and rear axles of the vehicle are driven by the wheel hub motors respectively.

[0090] Combining the formula for maximizing effective regenerative power with the formula for total wheel hub motor power generation and power battery charging efficiency, we obtain the following objective function for maximizing effective regenerative braking power:

[0091]

[0092] Among them, T regf 、T regr Respectively represent the electric braking torque of the front and rear wheels of the vehicle driven by the hub motor (the front wheel refers to the sum of the two front wheels, and the same applies to the rear wheel); μ mf 、μ mr Represents the power generation efficiency of the front and rear wheel motors respectively.

[0093] In a specific embodiment, the constraints include a maximum allowable battery charging power limit, a required vehicle braking torque, ECE regulations, and a hub motor braking characteristic limit.

[0094] Specifically, regarding the maximum allowable charging power limit of the battery, based on the battery's own charging characteristics, without considering the influence of temperature, different battery SOCs have different maximum allowable charging currents, and therefore different maximum allowable charging powers.

[0095] Regarding the required braking torque of the vehicle and the ECE regulations, the function of the braking system is to quickly respond to and execute the driver's braking intention. The braking force provided must not exceed the required braking torque, and the distribution of electric braking torque between the front and rear axles must not exceed the ECE regulations.

[0096] Regarding the braking characteristics of the hub motor, the maximum electric braking torque that the motor can output is limited by its own motor characteristic curve. When the speed is lower than the base speed, it can output constant torque, but when the speed is higher than the base speed, it can only output constant power. The hub motor can only play a limited role in the high-speed range.

[0097] The peak torque output by the hub motor meets the following requirements:

[0098]

[0099] In summary, the control variable T in this embodiment is regf 、T regr The following constraints need to be met:

[0100] For braking intensity conditions Z < 0.15, ECE regulations do not impose any restrictions on braking force distribution. In this case, the following conditions must be met:

[0101] 0<T regf <min(Treq-max , 2i·T mf-max )

[0102] 0<T regr <min(T req-max -T regf , 2i·T mr-max )

[0103] For braking intensity Z ≥ 0.15, the electric braking torque of the front and rear axles should be less than the torque distribution range specified by ECE regulations:

[0104] 0-T regf <min(T req-max , T f , 2i·T mf-max )

[0105] 0<T regr <min(T req-max -T regf , T r , 2i·T mr-max )

[0106] Among them, T req-max Indicates the battery charging power limiting torque; T mf-max 、T mr-max Respectively represent the limiting torque corresponding to the braking characteristics of the front and rear axle hub motors; T f 、T r Indicates the braking torque distributed to the front and rear axles.

[0107] As a preferred embodiment, in step S103, when any wheel slip rate exceeds the slip rate threshold, that is, when the vehicle has a locking tendency, in order to ensure the braking safety of the vehicle, Figure 4 As shown, Figure 4 The flowchart of an embodiment of the anti-lock braking control for a vehicle provided by the present invention includes:

[0108] Step S131: Determine the optimal slip ratio based on the slip ratio and road adhesion conditions.

[0109] Step S132: Determine a fully adjusted fuzzy controller based on the optimal slip ratio.

[0110] Step S133: performing anti-lock braking control on the vehicle according to the fully adjusted fuzzy controller.

[0111] In this embodiment, the optimal slip ratio is determined by the slip ratio and the road adhesion condition, so as to adjust the parameters of the fuzzy controller and thus implement anti-lock control of the vehicle.

[0112] In a specific embodiment, according to the optimal slip ratio, PID parameters are adjusted by trial and error to determine a fully adjusted fuzzy controller.

[0113] As a preferred embodiment, in step S132, in order to adjust the parameters in the fuzzy controller, the fuzzy controller determines the optimal slip rate of the current road condition based on the estimated value of the road adhesion coefficient, and adaptively adjusts the three parameters K of the PID controller according to different optimal slip rates. P , K I , K D , so that it can better complete the following control of the optimal slip rate and improve the robustness of the electric brake adjustment anti-lock control.

[0114] For the PID controller, the PID algorithm adjusts the control quantity u(t) by torque so that the actual slip rate y(t) tracks and approaches the desired slip rate r(t). Its time domain differential equation is:

[0115]

[0116] Among them, T I 、T D is the integral and differential time constant, K P is the proportionality coefficient.

[0117] In view of the engineering characteristics of this embodiment, a PI controller is selected to determine the electric brake adjustment torque of each wheel to track the slip rate, and the initial K is obtained by trial and error. P0 =6000,K IO =750.

[0118] The designed fuzzy control membership function is determined as follows: slip ratio difference E range [-0.2, 1], slip ratio difference change rate EC [-30, 30], ΔK P The range of variation is [-800, 800], ΔK I The range of change is [-100,100].

[0119] For the fuzzy controller, the specific control rules based on fuzzy parameter adjustment rules are shown in Tables 1 and 2 below.

[0120]

[0121] Table 1ΔK P Fuzzy control rule table

[0122]

[0123] Table 2ΔK P Fuzzy control rule table

[0124] Finally, the output data is defuzzified to obtain the exact PID parameter value ΔK P , ΔK I , so that the fuzzy PID controller can complete adaptive parameter adjustment under different road conditions, increasing the adaptability and robustness of the controller.

[0125] Through the above method, by monitoring the slip rate of each wheel of the vehicle, it is possible to effectively determine whether the vehicle has a tendency to lock. When the vehicle does not have a tendency to lock, the vehicle driving force is distributed through iterative calculation using modeling technology and PSO technology to maximize the vehicle's energy recovery efficiency. When the vehicle has a tendency to lock, in order to ensure the vehicle's braking safety, the vehicle is controlled by anti-lock control using a fuzzy adaptive PID composite anti-lock control algorithm to achieve vehicle safety control.

[0126] In order to solve the above problems, the present invention also provides a composite braking system for a vehicle driven by a hub motor, such as Figure 5 As shown, Figure 5 This is a schematic structural diagram of an embodiment of a compound braking system for a vehicle driven by an in-wheel motor provided by the present invention. The compound braking system 500 for a vehicle driven by an in-wheel motor includes:

[0127] The slip rate acquisition module 501 is used to obtain the slip rate of each wheel of the vehicle, the power generation efficiency MAP of the hub motor and the charging efficiency MAP of the battery;

[0128] an energy recovery module 502 for recovering energy from the vehicle based on the PSO according to the power generation efficiency MAP and the charging efficiency MAP when the slip rate of each wheel does not exceed the slip rate threshold;

[0129] The braking safety guarantee module 503 is configured to perform anti-lock control on the vehicle based on a fuzzy adaptive PID composite anti-lock control algorithm when the slip rate of any wheel exceeds a slip rate threshold.

[0130] The compound braking system 500 for a hub motor driven vehicle provided in the above embodiment implements the technical solution described in the above embodiment of the compound braking method for a hub motor driven vehicle. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above embodiment of the three-dimensional morphology model determination method, which will not be repeated here.

[0131] The present invention also provides a vehicle comprising the composite braking system of the vehicle driven by the wheel hub motor as described above.

[0132] It should be noted that a vehicle generally includes a vehicle control system and a vehicle hardware structure. Generally speaking, the vehicle control system includes the compound braking system of the in-wheel motor driven vehicle in this embodiment.

[0133] In summary, the compound braking method, system and vehicle for a hub motor-driven vehicle provided by the present invention can effectively determine whether the vehicle has a locking tendency by obtaining the slip rate of each wheel of the vehicle, the power generation efficiency MAP diagram of the hub motor and the charging efficiency MAP diagram of the battery. Therefore, when the vehicle does not have a locking tendency, the vehicle's energy recovery efficiency is maximized by optimizing the distribution of the vehicle's driving force. In addition, when the vehicle has a locking tendency, the vehicle is subjected to anti-lock control by a fuzzy adaptive PID compound anti-lock control algorithm to achieve safe control of the vehicle.

[0134] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. A composite braking method for a vehicle driven by an in-wheel motor, characterized in that: include: Obtain the slip rate of each wheel of the vehicle, the power generation efficiency MAP of the hub motor, and the charging efficiency MAP of the battery; When the slip rate of each wheel does not exceed the slip rate threshold, performing energy recovery on the vehicle based on the PSO according to the power generation efficiency MAP map and the charging efficiency MAP map; When any wheel slip rate exceeds the slip rate threshold, anti-lock control is performed on the vehicle based on a fuzzy adaptive PID composite anti-lock control algorithm.

2. The compound braking method for a vehicle driven by an in-wheel motor according to claim 1, characterized in that: Performing energy recovery on the vehicle based on the PSO according to the power generation efficiency MAP map and the charging efficiency MAP map includes: Constructing a parallel compound braking system model of the vehicle; determining an energy recovery efficiency optimization target for the vehicle according to the power generation efficiency MAP map and the charging efficiency MAP map; Energy recovery is performed on the vehicle based on the PSO according to the energy recovery efficiency optimization target and the slip rates of each wheel.

3. The compound braking method for a vehicle driven by an in-wheel motor according to claim 2, characterized in that: According to the energy recovery efficiency optimization target and the slip rates of each wheel, energy recovery is performed on the vehicle based on the PSO, including: determining a control variable according to the power generation efficiency MAP map and the charging efficiency MAP map; Determining an objective function and constraints based on the energy recovery efficiency optimization goal; Energy recovery is performed on the vehicle based on the PSO according to the slip rates of the wheels and the objective function.

4. The compound braking method for a vehicle driven by an in-wheel motor according to claim 3, characterized in that: The constraints include the maximum allowable charging power limit of the battery, the required braking torque of the vehicle, ECE regulations and the braking characteristics of the hub motor.

5. The compound braking method for a vehicle driven by an in-wheel motor according to claim 1, characterized in that: The vehicle is subjected to anti-lock braking control using a composite anti-lock braking control algorithm based on fuzzy adaptive PID, including: determining an optimal slip ratio based on the slip ratio and road adhesion conditions; determining a well-tuned fuzzy controller based on the optimal slip ratio; Anti-lock braking control is performed on the vehicle according to the well-adjusted fuzzy controller.

6. The compound braking method for a vehicle driven by an in-wheel motor according to claim 5, characterized in that: Based on the optimal slip ratio, a well-tuned fuzzy controller is determined, including: According to the optimal slip ratio, the PID parameters are adjusted by trial and error to determine a well-adjusted fuzzy controller.

7. The compound braking method for a vehicle driven by an in-wheel motor according to claim 1, characterized in that: Get the slip rate of each wheel of the vehicle, including: Obtaining the wheel speed of each wheel of the vehicle; The slip rate of each wheel is determined according to the wheel speed of each wheel and the reference vehicle speed.

8. The compound braking method for a vehicle driven by an in-wheel motor according to claim 7, characterized in that: Obtaining the wheel speed of each wheel of the vehicle, including: The wheel speed of each wheel of the vehicle is estimated and determined based on a federated Kalman filter.

9. A composite braking system for a vehicle driven by an in-wheel motor, characterized in that: include: The slip rate acquisition module is used to obtain the slip rate of each wheel of the vehicle, the power generation efficiency MAP of the hub motor and the charging efficiency MAP of the battery; an energy recovery module, configured to recover energy for the vehicle based on the PSO according to the power generation efficiency MAP map and the charging efficiency MAP map when the slip rate of each wheel does not exceed a slip rate threshold; The braking safety guarantee module is used to perform anti-lock control on the vehicle based on a fuzzy adaptive PID composite anti-lock control algorithm when any wheel slip rate exceeds the slip rate threshold.

10. A vehicle, characterized in that: A composite braking system for a vehicle driven by an in-wheel motor as claimed in claim 9.

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