Brake-by-wire and regenerative braking collaborative energy optimization method

Abstract

The invention provides a brake-by-wire and regenerative braking collaborative energy optimization method which comprises the following steps: S1, vehicle state parameters are acquired in real time, and the vehicle state parameters comprise a steering wheel angle, a yaw velocity and a vehicle speed; s2, on the basis of the vehicle state parameters and in combination with a preset vehicle dynamics model, a yaw moment safety boundary for maintaining stable driving of the vehicle under the current working condition is calculated in real time; s3, the total required braking torque corresponding to the braking intention of the driver is obtained; and S4, dynamically distributing the total demand braking torque between a regenerative braking system and a friction braking system of the vehicle. According to the invention, the maximum recovery of the braking energy can be realized on the premise of ensuring the dynamic stability of the vehicle.

Description

TECHNICAL FIELD

[0001] The application relates to a cooperative control method of a brake-by-wire system and a regenerative braking system applied to an electric vehicle, in particular to a brake-by-wire and regenerative braking cooperative energy optimization method, and belongs to the technical field of electric vehicle control. BACKGROUND

[0002] With the rapid development of new energy vehicle technology, electric vehicles have become an important direction of the automobile industry. In order to improve the cruising range, maximize the recovery of energy generated during braking of the vehicle, it is one of the core technologies of the energy management system of the electric vehicle. The regenerative braking system converts the driving motor into a generator, converts the kinetic energy of the vehicle into electrical energy and stores it in the battery, thereby realizing energy recovery.

[0003] In the brake-by-wire system, the driver's brake pedal input is no longer directly applied to the brake by a mechanical or hydraulic method, but is analyzed as a brake request signal, and the regenerative braking system and the traditional friction braking system are uniformly coordinated by the central controller of the vehicle to jointly meet the braking demand of the driver.

[0004] However, the existing cooperative braking strategy has inherent technical contradictions. Most strategies prioritize maximum energy recovery efficiency as the primary goal, i.e., preferentially using regenerative braking, and only supplementing with friction braking when the regenerative braking force is insufficient or in specific working conditions. This strategy performs well when braking in a straight line, but in some complex dynamic conditions, such as when the vehicle is turning while braking, it can pose a serious safety hazard. Specifically, the regenerative braking force is usually applied to the driving wheels. During turning, if too strong a regenerative braking force is applied to the driving wheels, it will significantly change the original balance of the vehicle's yaw moment, possibly weakening the vehicle's turning ability, reducing driving stability, and in severe cases, even inducing vehicle skidding or spin, leading to poor driving experience and serious safety risks.

[0005] Therefore, how to design a new type of cooperative braking strategy that can balance the relationship between energy recovery efficiency and vehicle driving stability in complex dynamic conditions, taking into account both safety and efficiency, is a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0006] Based on the above background, the purpose of the present application is to provide a brake-by-wire and regenerative braking cooperative energy optimization method that can maximize braking energy recovery while ensuring vehicle dynamic stability.

[0007] In order to achieve the above-mentioned purpose of the application, the present application provides the following technical solutions:

[0008] A brake-by-wire and regenerative braking cooperative energy optimization method, the method comprising the following steps:

[0009] S1, acquiring vehicle state parameters in real time, the vehicle state parameters including steering wheel angle, yaw rate and vehicle speed;

[0010] S2, calculating a yaw moment safety boundary for maintaining stable driving of the vehicle under current working conditions in real time based on the vehicle state parameters and in combination with a preset vehicle dynamics model;

[0011] S3, acquiring a total demand braking torque corresponding to braking intention of the driver;

[0012] S4, dynamically distributing the total demand braking torque between a regenerative braking system and a friction braking system of the vehicle;

[0013] The regenerative braking system can independently control regenerative braking torques applied to left and right drive wheels of the vehicle, and the dynamic distribution is optimized in real time with the maximum total regenerative braking torque as an optimization objective and while meeting a first constraint condition and a second constraint condition, the first constraint condition being that a value of a total yaw moment generated by the torques distributed to the regenerative braking system and the friction braking system on each wheel is within the yaw moment safety boundary, and the second constraint condition being that a sum of braking torques generated by the torques distributed to the regenerative braking system and the friction braking system on all wheels is equal to the total demand braking torque.

[0014] By quantifying dynamic stability of the vehicle as the yaw moment safety boundary that can be calculated in real time and taking it as a strong constraint condition of the braking torque distribution optimization problem, the strategy of recycling first and remedying later in the prior art is changed into a new mode of seeking optimal recycling within the safety boundary, ensuring that an output of any braking strategy does not threaten driving stability of the vehicle.

[0015] As a preference, in the step S2, the yaw moment safety boundary is determined according to a deviation between an expected value and an actual value of the yaw rate and an estimated value of a tire side slip angle.

[0016] The deviation between the expected value and the actual value of the yaw rate directly reflects whether a steering state of the vehicle meets an expectation of the driver, and the tire side slip angle is a key index for measuring whether a tire lateral force is close to a saturation limit, so the two core parameters are combined to calculate the safety boundary, so that the safety boundary is set neither too conservatively to affect energy recycling nor too aggressively to bring safety risks.

[0017] As a preference, the estimated value of the tire side slip angle is obtained by real-time estimation through a Kalman filtering algorithm by fusing lateral acceleration, yaw rate and steering wheel angle data of the vehicle.

[0018] The Kalman filter algorithm can effectively filter out sensor noise and fuse information of multiple related physical quantities, so that an accurate and rapid response side slip angle estimation value is obtained.

[0019] Preferably, in the step S2, the vehicle dynamics model is a two-degree-of-freedom or higher-degree-of-freedom vehicle dynamics model containing tire lateral force nonlinear characteristics.

[0020] When the vehicle approaches the instability limit, the lateral force of the tire and the side slip angle present a strong nonlinear relationship, that is, after the side slip angle increases to a certain extent, the lateral force no longer increases or even decreases. By using a vehicle dynamics model capable of describing such nonlinear characteristics, it can be ensured that the calculated yaw moment safety boundary is still accurate and effective under extreme working conditions.

[0021] Preferably, the tire lateral force nonlinear characteristics are described by a magic formula tire model or a Dugoff tire model.

[0022] Preferably, when the vehicle state parameters obtained in the step S1 indicate that the vehicle is in a steering working condition, in the dynamic distribution process of the step S4, the regenerative braking torque on the inner side of the steering wheel is preferentially reduced, and the regenerative braking torque on the outer side of the steering wheel and / or the friction braking torque of the front and rear axles are correspondingly increased, so that the total yaw moment meets the first constraint condition.

[0023] When steering, the vertical load of the inner side wheel decreases, and the adhesion it can provide also decreases. Excessive regenerative braking torque applied to the wheel easily leads to breaking the adhesion limit, thereby generating an unstable yaw moment. By using the inner reduction and outer compensation distribution strategy, the yaw moment adjustment can be kept within the safety zone without affecting the total braking force.

[0024] Preferably, the real-time optimization of the dynamic distribution is realized by solving a quadratic programming model with inequality constraints.

[0025] Preferably, the objective function of the quadratic programming model is the minimization of the sum of squares of the regenerative braking torques, the inequality constraint of the quadratic programming model is the first constraint condition, and the equality constraint of the quadratic programming model is the second constraint condition.

[0026] Preferably, the method further comprises the following steps:

[0027] If it is determined that the anti-lock braking system or the traction control system of the vehicle is activated, the regenerative braking torque of the side wheel is set to zero or limited within a preset low safety threshold.

[0028] Compared with the prior art, the present application has the following advantages:

[0029] The line control brake and regenerative braking cooperative energy optimization method of the application solves the inherent contradiction between energy recovery and driving stability under complex dynamic conditions such as steering braking, and can maximize the recovery of braking energy on the premise of ensuring that the vehicle does not have the risk of instability, thereby significantly improving the comprehensive energy efficiency and active control safety of the vehicle in real driving scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the provided drawings.

[0031] Figure 1 is a flowchart of the line control brake and regenerative braking cooperative energy optimization method of the application;

[0032] Figure 2 is a schematic diagram of the yaw moment safety boundary in the application. DETAILED DESCRIPTION

[0033] The technical solutions of the present application will be further described in detail below by specific embodiments, and in combination with the drawings. It should be understood that the implementation of the present application is not limited to the following embodiments, and any form of modification and / or change of the present application will fall within the scope of protection of the present application.

[0034] In the present application, unless otherwise specified, all parts and percentages are weight units, and the equipment and raw materials used can be purchased from the market or commonly used in the art. The methods in the following examples are conventional methods in the art, unless otherwise specified. The components or equipment in the following examples are general standard components or components known to those skilled in the art, and their structure and principles can be known to those skilled in the art through technical manuals or through conventional experimental methods.

[0035] The embodiments of the present application will be described in detail below in combination with the drawings. In the following detailed description, many specific details are set forth in order to provide a thorough understanding of the embodiments of the present application. However, one or more embodiments can be implemented by those skilled in the art without these specific details.

[0036] The embodiments of the present application disclose a line control brake and regenerative braking cooperative energy optimization method, referring to Figure 1 The method comprises the following steps:

[0037] S1, acquiring vehicle state parameters in real time, the vehicle state parameters including steering wheel angle, yaw rate and vehicle speed;

[0038] S2, calculating a yaw moment safety boundary for maintaining stable driving of the vehicle under the current working condition in real time based on the vehicle state parameters and in combination with a preset vehicle dynamics model;

[0039] S3, acquiring a total demand braking torque corresponding to the braking intention of the driver;

[0040] S4, dynamically distributing the total demand braking torque between a regenerative braking system and a friction braking system of the vehicle;

[0041] The regenerative braking system can independently control regenerative braking torques applied to left and right drive wheels of the vehicle, and the dynamic distribution is optimized in real time with the optimization objective of maximizing the total regenerative braking torque while satisfying the first constraint condition and the second constraint condition, the first constraint condition being that a value of the total yaw moment generated by the torques distributed to the regenerative braking system and the friction braking system on each wheel is within the yaw moment safety boundary, and the second constraint condition being that a sum of braking torques generated by the torques distributed to the regenerative braking system and the friction braking system on all wheels is equal to the total demand braking torque.

[0042] The above steps will be described in detail below.

[0043] Step S1, acquiring vehicle state parameters in real time.

[0044] During driving of the vehicle, the controller collects a series of sensor signals reflecting the dynamics of the vehicle in real time at a very high frequency through the vehicle CAN bus. In the embodiment, the vehicle state parameters that must be acquired at least include:

[0045] steering wheel angle δ w measured by a steering wheel angle sensor, directly reflecting the steering intention of the driver.

[0046] yaw rate γ, measured by a gyroscope sensor in an inertial measurement unit (IMU), reflecting the actual angular velocity of the vehicle rotating around its vertical axis.

[0047] vehicle speed v x calculated from wheel speed sensor signals or obtained from GPS signals.

[0048] In addition, in order to perform more accurate calculation, lateral acceleration a y , wheel speeds ω i of the wheels and other parameters can also be acquired.

[0049] Step S2, calculating a yaw moment safety boundary.

[0050] The controller determines a safe range of additional yaw moment that can be applied to the vehicle based on the vehicle state parameters obtained in step S1 and the vehicle dynamics model pre-stored in the memory of the controller.

[0051] First, the controller needs to calculate the desired yaw rate γ des , which represents the ideal steady-state response of the vehicle at the current speed and steering wheel angle. It is calculated as follows:

[0052] where L is the wheelbase of the vehicle, K is the understeer gradient, and is a constant related to the vehicle's own characteristics.

[0053] Then, the controller estimates the slip angle α i of each tire. Since the slip angle cannot be directly measured, the Extended Kalman Filter (EKF) algorithm is used to estimate it in this embodiment. The state variables of the EKF algorithm are set as the sideslip angle β and the yaw rate γ of the vehicle, and the observation variables are the lateral acceleration a y and the yaw rate γ directly measured by the sensors. Through the prediction and update iterations of the EKF algorithm, a more accurate estimate of the vehicle's sideslip angle β is obtained, and then the slip angle α i of each tire is calculated based on the geometric relationship and kinematic relationship of the vehicle.

[0054] Next, the safe boundary is calculated using the vehicle dynamics model. This embodiment uses a two-degree-of-freedom vehicle model that includes the nonlinear characteristics of the tires, specifically the Magic Formula tire model, which can accurately describe the nonlinear relationship between the tire lateral force F y and the tire slip angle α and the vertical load F z :

[0055]

[0056] where B, C, D, and E are tire characteristic parameters.

[0057] The controller determines whether the lateral force of each tire is close to its adhesion limit based on the estimated tire slip angle α i and the tire model. The calculation of the yaw moment safety boundary takes into account the deviation of the yaw rate and the working state of the tires. The calculation formula is as follows:

[0058]

[0059] where μ is the estimate of the road adhesion coefficient. When the yaw rate deviation increases or any tire slip angle approaches the saturation region, the safety boundary narrow dynamically. Please refer to Figure 2The figure illustrates that the safety boundary is a dynamic range that varies with vehicle speed and steering angle, and the total yaw moment generated by the vehicle must fall within this safety range.

[0060] The embodiment also contains real-time estimation of road adhesion coefficient μ. The controller calculates the slip ratio of the wheels by comparing the theoretical angular acceleration of the drive wheels (calculated from motor torque and moment of inertia) with the actual angular acceleration measured by the wheel speed sensor. When the slip ratio abnormally increases, it indicates that the road is relatively wet. By establishing a mapping table of slip ratio and adhesion coefficient, the real-time estimation of μ can be realized, and it can be used to dynamically adjust the yaw moment safety boundary, so that the method is still safe and effective on low adhesion roads such as rain and snow.

[0061] Step S3, obtain the total demand braking torque.

[0062] The controller converts the driver's physical operation into an explicit total demand braking torque T req_total by reading the signal of the brake pedal displacement sensor or pressure sensor, and consulting the pre-set braking intention mapping table in the controller in combination with the current vehicle speed.

[0063] Step S4, real-time optimization with constraints.

[0064] The problem that the controller needs to solve is how to allocate the total demand braking torque T req_total to the regenerative braking torques T reg_fl , T reg_fr of the four wheels (assuming a front-drive vehicle) and the friction braking torques T fric_fl , T fric_fr , T fric_rl , T fric_rr . The embodiment constructs this problem as a quadratic programming model.

[0065] The optimization objective is to maximize the total regenerative braking torque (equivalent to minimizing the sum of squares of regenerative braking torques). The calculation formula is:

[0066]

[0067] Where w1 and w2 are weight coefficients.

[0068] The first constraint condition is:

[0069]

[0070] Where B f , B r are the front and rear wheel tracks, and ΔM z,min , ΔM z,max are the lower and upper limits of the yaw moment safety boundary calculated in step S2. This formula calculates the total yaw moment generated by all braking forces.

[0071] The second constraint condition is:

[0072]

[0073] The other physical constraints are: the friction braking torque of each wheel is non-negative and is not greater than its maximum capability; the regenerative braking torque of each driving wheel is non-negative and is not greater than the maximum power generation torque under the current working condition of the motor.

[0074] The controller inputs the above model into a solver, and in each calculation cycle, a set of optimal torque distribution values can be obtained.

[0075] The working principle of the application is illustrated by taking the case of a vehicle turning left while braking.

[0076] When the vehicle is turning left, according to steps S1 and S2, the system judges that the vehicle is in the turning condition and calculates the corresponding yaw torque safety boundary. At this time, if the average distribution of regenerative braking force is still used, the vertical load of the left front wheel (the turning inner side driving wheel) is reduced due to load transfer, and the applied regenerative braking force is easy to saturate the lateral force, thereby generating an undesirable yaw torque that interferes with the turning and may touch the safety boundary.

[0077] The optimal solution is searched under the restriction of the first constraint condition, and the result is to preferentially reduce the regenerative braking torque T reg_fl of the left front wheel and even reduce it to zero. In order to meet the second constraint condition (the total braking force is unchanged), the lost part of the braking force is compensated by increasing the regenerative braking torque T reg_fr of the right front wheel and / or correspondingly increasing the friction braking torque of the four wheels. The distribution result is that the total yaw torque generated finally is accurately controlled within the safety boundary, the vehicle stably passes the curve according to the intention of the driver, and at the same time, the total energy recovery also reaches the maximum value under the safety premise.

[0078] In addition, the method also includes a step of linkage with an underlying safety system.

[0079] For the highest safety guarantee, the controller will continuously monitor the status flag bits of the ABS and TCS systems. Once it is shown in the CAN message that the ABS or TCS of any wheel is activated, the controller will immediately execute an interruption program, forcibly set the regenerative braking torque T reg_i of the wheel to zero, and completely entrust the friction braking system with the braking torque required by the wheel.

[0080] The method solves the inherent contradiction between energy recovery and driving stability under complex dynamic working conditions such as steering braking by calculating the yaw moment safety boundary of the vehicle in real time and optimizing the real-time distribution of regenerative braking torque and friction braking torque with the yaw moment safety boundary as a strong constraint, and can maximize the recovery of braking energy on the premise of ensuring that the vehicle does not have the risk of instability, thereby significantly improving the comprehensive energy efficiency and active control safety of the vehicle under real driving scenarios.

[0081] The principles and implementation modes of the present application are described herein by using specific examples, and the above examples are only used to help understand the method of the present application and its core idea. It should be pointed out that for ordinary skilled persons in the art, some improvements and modifications can be made to the present application without departing from the principles of the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

Claims

1. A method of brake-by-wire and regenerative braking cooperative energy optimization, characterized in that: The method comprises the following steps: S1, acquiring vehicle state parameters in real time, wherein the vehicle state parameters comprise a steering wheel angle, a yaw rate and a vehicle speed; S2, calculating a yaw moment safety boundary for maintaining stable driving of the vehicle under a current working condition in real time based on the vehicle state parameters and in combination with a preset vehicle dynamics model; S3, acquiring a total demand braking torque corresponding to a braking intention of a driver; S4, dynamically distributing the total demand braking torque between a regenerative braking system and a friction braking system of the vehicle; wherein the regenerative braking system can independently control regenerative braking torques applied to left and right drive wheels of the vehicle, the dynamic distribution is optimized in real time with a maximum total regenerative braking torque as an optimization target and while satisfying a first constraint condition and a second constraint condition, the first constraint condition is that a value of a total yaw moment generated by the torques distributed to the regenerative braking system and the friction braking system on each wheel is within the yaw moment safety boundary, and the second constraint condition is that a sum of braking torques generated by the torques distributed to the regenerative braking system and the friction braking system on all wheels is equal to the total demand braking torque.

2. The method of claim 1, wherein: In the step S2, the yaw moment safety boundary is determined according to a deviation between an expected value and an actual value of the yaw rate and an estimated value of a tire side slip angle.

3. The method of claim 2, wherein: The estimated value of the tire side slip angle is obtained by real-time estimation through a Kalman filtering algorithm by fusing vehicle lateral acceleration, yaw rate and steering wheel angle data.

4. The method of claim 1, wherein: In the step S2, the vehicle dynamics model is a two-degree-of-freedom or higher-degree-of-freedom vehicle dynamics model containing tire lateral force nonlinear characteristics.

5. The method of claim 4, wherein: The tire lateral force nonlinear characteristics are described by a magic formula tire model or a Dugoff tire model.

6. The method of claim 1, wherein: When the vehicle state parameters acquired in the step S1 indicate that the vehicle is in a steering working condition, in the dynamic distribution process of the step S4, the regenerative braking torque on the inside drive wheel of the steering is preferentially reduced, and the regenerative braking torque on the outside drive wheel of the steering and / or the friction braking torque of the front and rear axles are correspondingly increased, so that the total yaw moment satisfies the first constraint condition.

7. The method of claim 1, wherein: The real-time optimization of the dynamic distribution is realized by solving a quadratic programming model with inequality constraints.

8. The method of claim 7, wherein: The objective function of the quadratic programming model is minimization of a regenerative braking torque square sum, the inequality constraint of the quadratic programming model is the first constraint condition, and the equality constraint of the quadratic programming model is the second constraint condition.

9. The method of claim 1, wherein: The method further comprises the following steps: If it is determined that an anti-lock braking system or a traction control system of the vehicle is activated, the regenerative braking torque of the activated side wheel is set to zero or limited within a preset low safety threshold.

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