A pressure sensor-free control method for an electric vehicle's electronic mechanical brake system

Abstract

The present invention provides a pressure-free sensor control method for an electric vehicle electronic mechanical brake system, comprising: step S1, obtaining the inherent parameters of a drive motor and the operating data of the drive motor when a braking action is generated, and obtaining the load torque through a dynamic torque balance equation; step S2, obtaining the transmission data of a transmission structure connected to the drive motor, and obtaining a first clamping force estimation value according to the transmission data and the load torque; step S3, based on the viscous effect between a friction plate and a brake disc, obtaining the rotor angle of the drive motor and obtaining a second clamping force estimation value through a characteristic curve dynamic stiffness model; step S4, introducing variance and calculating the first clamping force estimation value and the second clamping force estimation value based on the minimum variance principle to obtain an optimal clamping force estimation value. The beneficial effect is that the present invention can use a pressure-free sensor control strategy to estimate the clamping force generated in real time and replace the pressure sensor, thereby reducing costs and improving braking performance.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicles, and in particular to a pressure-sensor-free control method for an electric vehicle electronic mechanical brake system. Background Art

[0002] With the continuous development of motors, batteries, and electric drive technologies, more and more wire-controlled technologies have emerged to replace traditional mechanical control technologies. The electromechanical brake (EMB) system has gradually become the first choice for the next generation of electric vehicle braking technology due to its advantages such as intelligence, lightweight, and high safety.

[0003] Compared with traditional hydraulic brakes, the EMB system adopts a mechatronics design, eliminates complex hydraulic pipelines, has a simpler structure, and is clean and environmentally friendly. Since it does not rely on brake fluid, the EMB system avoids the resulting braking delay and has a faster response speed. In addition, the EMB system can accurately control the required braking force, significantly improving the safety and reliability of the vehicle.

[0004] However, under actual braking conditions, the strain gauge of the pressure sensor will be frequently squeezed. Under long-term fatigue use, the strain gauge may break, causing the pressure sensor to fail, and its reliability cannot be guaranteed. Secondly, a large amount of heat is generated when the friction plate contacts the brake disc. Under extremely high temperatures, the clamping force measured by the pressure sensor may be different from the actual one, resulting in failure to meet braking requirements and affecting personal safety.

[0005] In order to avoid the pressure sensor in the EMB system from experiencing a decrease in accuracy or even failure, which would result in the inability to provide the clamping force required by the electric vehicle, how to use a pressure sensor-free control strategy to estimate the clamping force generated in real time and replace the pressure sensor is an urgent problem to be solved. Summary of the invention

[0006] The technical problem to be solved by the present invention is to adopt a pressure-sensor-free control strategy to estimate the clamping force generated in real time and replace the pressure sensor, thereby reducing costs and improving braking performance. In order to overcome the defects of the above-mentioned prior art (or related technology), the present invention provides a pressure-sensor-free control method for an electric vehicle electronic mechanical braking system.

[0007] The present invention provides a pressure sensor-free control method for an electric vehicle electronic mechanical brake system, comprising:

[0008] Step S1, for an electronic mechanical braking system in an electric vehicle, obtaining inherent parameters of a driving motor in the electronic mechanical braking system and operating data of the driving motor when a braking action is generated, and calculating the load torque by using the inherent parameters and the operating data through a dynamic torque balance equation;

[0009] Step S2, acquiring transmission data of the transmission structure connected to the drive motor, and obtaining a first clamping force estimation value according to the transmission data and the load torque;

[0010] Step S3, based on the viscous effect between the friction plate and the brake disc in the electronic mechanical brake system, obtaining the rotor angle of the drive motor and analyzing the rotor angle through a characteristic curve dynamic stiffness model to obtain a second clamping force estimation value;

[0011] Step S4, introducing the variance of the first clamping force estimation value and the second clamping force estimation value, and based on the minimum variance principle, calculating the first clamping force estimation value and the second clamping force estimation value to obtain an optimal clamping force estimation value, and feeding back the optimal clamping force estimation value to the electronic mechanical braking system so that the drive motor drives the friction plate to press the brake disc with the optimal clamping force estimation value.

[0012] Compared with the prior art, the pressure sensor-free control method of the electric vehicle electronic mechanical brake system of the present invention has the following advantages:

[0013] The present invention firstly considers the dynamic torque balance equation of the drive motor, estimates the load torque of the drive motor in real time by receiving the operating data fed back from the sensor in combination with the inherent parameters, then calculates the first clamping force estimate value according to the transmission data of the transmission structure connected to the drive motor, and takes into account the viscosity effect between the friction plate and the brake disc, calculates the second clamping force estimate value through the characteristic curve dynamic stiffness model, and finally configures the variance of the two clamping force estimate values, and optimally estimates the clamping force estimate value to obtain the optimal clamping force estimate value, which greatly improves the accuracy of the clamping force estimation, and by designing a pressure-free sensor algorithm instead of a pressure sensor, optimally estimates the clamping force generated when the electronic mechanical brake system is working in real time, solves the problem that the pressure sensor is high in cost and the clamping force measurement under harsh braking conditions has a reduced accuracy or even an overall failure, thereby causing a reduction in the braking performance of the electric vehicle.

[0014] In a possible implementation, the step S1 includes:

[0015] Step S11, for the electronic mechanical braking system in the electric vehicle, obtaining the number of motor pole pairs and the motor flux of the drive motor as the inherent parameters, and obtaining the moment of inertia, angular velocity, q-axis current, friction torque and rotor angle of the drive motor when the braking action is generated as the operating data;

[0016] Step S12, based on the dynamic torque balance equation, the load torque is obtained according to the number of motor pole pairs, the motor flux, the moment of inertia, the angular velocity, the q-axis current, the friction torque and the rotor angle.

[0017] In a possible implementation, in step S12, the load torque is obtained by the following calculation formula:

[0018] ;

[0019] in,

[0020] represents the moment of inertia;

[0021] represents the time derivative of the angular velocity;

[0022] represents the angular velocity;

[0023] represents the electromagnetic torque of the driving motor;

[0024] represents the load moment;

[0025] represents the friction torque;

[0026] represents the number of pole pairs of the motor;

[0027] represents the motor flux;

[0028] represents the magnitude of the q-axis current;

[0029] represents the Coulomb friction coefficient;

[0030] represents the first clamping force estimate;

[0031] represents the offset coefficient;

[0032] represents a symbolic function;

[0033] represents the rotor angle;

[0034] represents the derivative of the rotor angle with respect to time.

[0035] In a possible implementation, step S2 includes:

[0036] Step S21, obtaining the ball screw lead, the planetary gear main reduction ratio, the planetary gear transmission efficiency and the ball screw transmission efficiency of the transmission structure connected to the drive motor as the transmission data;

[0037] Step S22, obtaining a relationship between the first clamping force estimation value and the load torque according to the ball screw lead, the planetary gear main reduction ratio, the planetary gear transmission efficiency and the ball screw transmission efficiency;

[0038] Step S23: obtaining the first clamping force estimation value according to the relationship and the load moment.

[0039] In a possible implementation, in step S22, the relationship is obtained by the following calculation formula:

[0040] ;

[0041] in,

[0042] represents the load moment;

[0043] represents the first clamping force estimate;

[0044] represents the lead of the ball screw;

[0045] represents the planetary gear main reduction ratio;

[0046] represents the transmission efficiency of the planetary gear;

[0047] Indicates the transmission efficiency of the ball screw.

[0048] In a possible implementation, in step S23, the first clamping force estimation value is obtained by the following calculation formula:

[0049] ;

[0050] in,

[0051] represents the first clamping force estimate;

[0052] represents the magnitude of the q-axis current;

[0053] represents the motor flux;

[0054] represents the number of pole pairs of the motor;

[0055] represents the moment of inertia;

[0056] represents the time derivative of the angular velocity;

[0057] represents the offset coefficient;

[0058] represents a symbolic function;

[0059] represents the derivative of the rotor angle with respect to time;

[0060] represents the lead of the ball screw;

[0061] represents the planetary gear main reduction ratio;

[0062] represents the transmission efficiency of the planetary gear;

[0063] Indicates the transmission efficiency of the ball screw;

[0064] represents the Coulomb friction coefficient.

[0065] In a possible implementation, step S3 includes:

[0066] Step S31, based on the viscous effect between the friction plate and the brake disc in the electronic mechanical brake system, obtaining the rotor angle of the drive motor and obtaining the transfer function of the characteristic curve dynamic stiffness model according to the linear relationship between the second clamping force estimation value and the rotor angle;

[0067] Step S32, obtaining an expression of the estimated value of the second clamping force in the real number domain according to the transfer function;

[0068] Step S33: Based on the expression, convert the linear relationship between the second clamping force estimation value and the rotor angle into a polynomial relationship to obtain the second clamping force estimation value.

[0069] In a possible implementation, in step S31, the transfer function is obtained by the following calculation formula:

[0070] ;

[0071] in,

[0072] represents the transfer function;

[0073] an expression representing the estimated value of the second clamping force in the complex domain;

[0074] An expression representing the rotor angle in the complex domain;

[0075] a linear coefficient representing the second clamping force estimate and the rotor angle;

[0076] represents the time constant;

[0077] represents a complex function.

[0078] In a possible implementation, in step S33, the second clamping force estimation value is obtained by the following calculation formula:

[0079] ;

[0080] in,

[0081] represents the second clamping force estimated value;

[0082] Represents the preset polynomial coefficients;

[0083] represents the rotor angle;

[0084] represents the time constant;

[0085] represents the time derivative of the second clamping force estimate.

[0086] In a possible implementation, in step S4, the optimal clamping force estimation value is obtained by the following calculation formula:

[0087] ;

[0088] in,

[0089] represents the optimal clamping force estimation value;

[0090] represents the first clamping force estimate;

[0091] represents a variance of the first clamping force estimate;

[0092] represents a variance of the second clamping force estimate;

[0093] represents the second clamping force estimate value. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 is a flow chart of the steps of the present invention;

[0095] Figure 2 is a specific flow chart of step S1 of the present invention;

[0096] Figure 3 is a specific flow chart of step S2 of the present invention;

[0097] Figure 4 It is a specific flow chart of step S3 of the present invention. DETAILED DESCRIPTION

[0098] First, those skilled in the art should understand that these implementations are only used to explain the technical principles of the embodiments of the present invention, and are not intended to limit the protection scope of the embodiments of the present invention. Those skilled in the art can make adjustments to them as needed to adapt to specific application scenarios.

[0099] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0100] See also Figure 1 The embodiment of the present invention discloses a pressure sensor-free control method for an electric vehicle electronic mechanical braking system, comprising:

[0101] The first step is to estimate the load torque through the dynamic torque balance equation: based on the inherent parameters of the drive motor and the angular velocity of the drive motor during braking, the q-axis current and other operating data, the external load torque is estimated through the dynamic torque balance equation;

[0102] The second step is to estimate the clamping force according to the load torque and the transmission structure: the first clamping force estimation value is estimated in real time according to the planetary gear and the ball screw reduction ratio and the transmission efficiency connected to the external rotating shaft of the driving motor and the load torque estimated in the first step;

[0103] The third step is to estimate the clamping force through the characteristic curve dynamic stiffness model (the model comes from the literature: "Hybrid Genetic Algorithm and Kalman Filter Approach to Estimate the Clamping Force of Electro-Mechanical Brake"): When the EMB system is working, the characteristic curve dynamic stiffness model between the clamping force and the motor rotor angle is used to calculate the size of the second clamping force estimate at this moment in real time through the value returned by the motor rotor position encoder and the second clamping force estimate calculated at the previous moment;

[0104] The fourth step is the fusion estimation of the clamping force: under the braking condition of the vehicle, the ECU receives the signal of the brake pedal being pressed and calculates the required target clamping force based on the degree to which the brake pedal is pressed. At this time, the EMB system starts to work, driving the ball screw through the drive motor to make the friction plate press the brake disc to generate clamping force. According to the first clamping force estimate value and the second clamping force estimate value estimated by the algorithm in the second and third steps, the variance of the two clamping force estimates is set to fuse and estimate the optimal clamping force estimate value.

[0105] See also Figure 2 , the first step includes:

[0106] (1) A permanent magnet synchronous motor is selected as the drive motor, and the d-axis current is used control strategies;

[0107] (2) According to the dynamic torque balance equation, we get:

[0108] ;

[0109] In the formula, Indicates the rotational inertia of the drive motor; Indicates the angular velocity of the drive motor; It represents the derivative of the motor rotor angular velocity with respect to time; Represents the electromagnetic torque of the driving motor, and its magnitude is ,in is the number of motor pole pairs, represents the motor flux, Indicates the q-axis current of the drive motor, represents the load moment, Indicates the friction torque inside the drive motor;

[0110] (3) Simplify the internal friction torque of the motor and express it in the form of load torque to obtain:

[0111] ;

[0112] In the formula, represents the Coulomb friction coefficient; represents the offset coefficient; represents a first clamping force estimation value to be estimated; Represents a symbolic function expression; Indicates the motor rotor angle; represents the derivative of the rotor angle with respect to time, where the first clamping force estimate exists as an unknown parameter.

[0113] See also Figure 3 , the second step includes:

[0114] (1) During the actual braking process, the drive motor decelerates and increases torque through the planetary gear, and then the ball screw presses the brake disc to achieve braking;

[0115] (2) Based on the planetary gear main reduction ratio, planetary gear transmission efficiency and ball screw lead, the relationship between the second clamping force estimate and the load torque can be obtained:

[0116] ;

[0117] In the formula, represents the load moment; represents a first clamping force estimation value to be estimated; Indicates the lead of the ball screw; Indicates the planetary gear main reduction ratio; Indicates the transmission efficiency of planetary gears; Indicates the ball screw transmission efficiency;

[0118] (3) Combine the expression in the first step The estimated value of the clamping force, i.e. the first estimated value of the clamping force, can be obtained:

[0119] ;

[0120] In the formula, Indicates the magnitude of the q-axis current; Indicates the motor flux; Indicates the number of motor pole pairs; Indicates the motor's moment of inertia; It represents the derivative of the motor rotor angular velocity with respect to time; represents the offset coefficient; Represents a symbolic function expression; represents the derivative of the rotor angle with respect to time; represents the Coulomb friction coefficient;

[0121] (4) In order to facilitate computer programming, it is expressed in a discretized form:

[0122] ;

[0123] In the formula, represents the first clamping force estimate at time k; , They represent the angular velocity of the motor rotor at time k-1 and time k respectively; , Indicates the motor rotor angle at time k-1 and time k.

[0124] See also Figure 4 , the third step includes:

[0125] (1) When the EMB is working, the second clamping force estimation value is estimated by the characteristic curve dynamic stiffness model, taking into account the "viscous effect" between the friction pad and the brake disc during braking;

[0126] (2) During the tightening process, if the clamping force is linearly related to the motor rotor angle and the "viscous effect" is taken into account, the transfer function of the characteristic curve dynamic stiffness model can be obtained:

[0127] ;

[0128] In the formula, represents the transfer function; an expression representing the estimated value of the second clamping force in the complex domain; The expression representing the motor rotor angle in the complex domain; Indicates clamping force The angle of the motor rotor The linear coefficient of represents the time constant; represents a complex function;

[0129] (3) From the transfer function of the characteristic curve dynamic stiffness model, the expression for the estimated value of the second clamping force in the real number domain can be obtained:

[0130] ;

[0131] In the formula, Indicates the motor rotor angle; represents a derivative of the second clamping force estimate with respect to time;

[0132] (4) During the actual braking process, the second clamping force estimate is expressed as the motor rotor angle The polynomial relationship of is obtained, so the clamping force expression closer to the actual situation is obtained:

[0133] ;

[0134] In the formula, are the polynomial coefficients;

[0135] (5) In order to facilitate computer programming, it is represented and simplified into a discrete form:

[0136] ;

[0137] In the formula, represents the discretized polynomial coefficients; , They represent the estimated values ​​of the second clamping force at time k-1 and time k respectively.

[0138] Continue to see Figure 1 , the fifth step includes:

[0139] (1) Under vehicle braking conditions, the ECU receives the brake pedal pressing signal and calculates the required target clamping force based on the degree to which the brake pedal is pressed. At this time, the EMB system starts to work, driving the ball screw through the drive motor to make the friction plate press the brake disc to generate clamping force;

[0140] (2) At this time, the q-axis current is obtained in real time through the sensor , motor rotor angle , motor rotor angular velocity Combining the algorithms in the second and third steps, the optimal clamping force estimate can be calculated in real time. Estimated value of , ;

[0141] (3) Taking into account external interference and sensor inaccuracy, the actual estimated clamping force , There is Gaussian noise in the process, let the estimated value , The variances of , ;

[0142] (4) Based on the minimum variance principle and by configuring in advance in the algorithm , The optimal clamping force estimate can be calculated The values ​​are:

[0143] ;

[0144] (5) Finally, under braking conditions, the optimal clamping force estimate is calculated in real time. Replaces the pressure sensor and serves as the feedback value of the force closed loop and the required target clamping force Subtract the two to get the input of the outer loop, and through the subsequent PI control, input the required q-axis current The motor is rotated to drive the ball screw for braking, thus realizing a pressure sensor-free control method.

[0145] In the description of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "in the present embodiment", "specific example", or "some examples" etc. means that the specific features, mechanisms, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, mechanisms, materials or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0146] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A pressure sensorless control method for an electric vehicle electronic mechanical brake system, characterized in that: The following steps are involved: Step S1, for an electronic mechanical braking system in an electric vehicle, obtaining inherent parameters of a driving motor in the electronic mechanical braking system and operating data of the driving motor when a braking action is generated, and calculating the load torque by using the inherent parameters and the operating data through a dynamic torque balance equation; Step S2, acquiring transmission data of the transmission structure connected to the drive motor, and obtaining a first clamping force estimation value according to the transmission data and the load torque; Step S3, based on the viscous effect between the friction plate and the brake disc in the electronic mechanical brake system, obtaining the rotor angle of the drive motor and analyzing the rotor angle through a characteristic curve dynamic stiffness model to obtain a second clamping force estimation value; Step S4, introducing the variance of the first clamping force estimation value and the second clamping force estimation value, and calculating the first clamping force estimation value and the second clamping force estimation value based on the minimum variance principle to obtain an optimal clamping force estimation value, and feeding back the optimal clamping force estimation value to the electronic mechanical brake system so that the drive motor drives the friction plate to press the brake disc with the optimal clamping force estimation value; The step S1 comprises: Step S11, for the electronic mechanical braking system in the electric vehicle, obtaining the number of motor pole pairs and the motor flux of the drive motor as the inherent parameters, and obtaining the moment of inertia, angular velocity, q-axis current, friction torque and rotor angle of the drive motor when the braking action is generated as the operating data; Step S12, based on the dynamic torque balance equation, obtaining the load torque according to the number of motor pole pairs, the motor flux, the moment of inertia, the angular velocity, the q-axis current, the friction torque and the rotor angle; The step S3 comprises: Step S31, based on the viscous effect between the friction plate and the brake disc in the electronic mechanical brake system, obtaining the rotor angle of the drive motor and obtaining the transfer function of the characteristic curve dynamic stiffness model according to the linear relationship between the second clamping force estimation value and the rotor angle; Step S32, obtaining an expression of the estimated value of the second clamping force in the real number domain according to the transfer function; Step S33, based on the expression, converting the linear relationship between the second clamping force estimation value and the rotor angle into a polynomial relationship to obtain the second clamping force estimation value; In step S31, the transfer function is obtained by the following calculation formula: ； in, represents the transfer function; an expression representing the estimated value of the second clamping force in the complex domain; An expression representing the rotor angle in the complex domain; a linear coefficient representing the second clamping force estimate and the rotor angle; represents the time constant; represents a complex function; In the step S33, the second clamping force estimation value is obtained by the following calculation formula: ； in, represents the second clamping force estimated value; Represents the preset polynomial coefficients; represents the rotor angle; represents the time constant; represents the time derivative of the second clamping force estimate.

2. The pressure sensorless control method of the electric vehicle electronic mechanical brake system according to claim 1, characterized in that: In step S12, the load moment is obtained by the following calculation formula: ； in, represents the moment of inertia; represents the time derivative of the angular velocity; represents the angular velocity; represents the electromagnetic torque of the driving motor; represents the load moment; represents the friction torque; represents the number of pole pairs of the motor; represents the motor flux; represents the magnitude of the q-axis current; represents the Coulomb friction coefficient; represents the first clamping force estimate; represents the offset coefficient; represents a symbolic function; represents the rotor angle; represents the derivative of the rotor angle with respect to time.

3. The pressure sensorless control method of the electric vehicle electronic mechanical brake system according to claim 2 is characterized in that: The step S2 comprises: Step S21, obtaining the ball screw lead, the planetary gear main reduction ratio, the planetary gear transmission efficiency and the ball screw transmission efficiency of the transmission structure connected to the drive motor as the transmission data; Step S22, obtaining a relationship between the first clamping force estimation value and the load torque according to the ball screw lead, the planetary gear main reduction ratio, the planetary gear transmission efficiency and the ball screw transmission efficiency; Step S23: obtaining the first clamping force estimation value according to the relationship and the load moment.

4. The pressure sensorless control method for the electric vehicle electronic mechanical brake system according to claim 3 is characterized in that: In step S22, the relationship is obtained by the following calculation formula: ； in, represents the load moment; represents the first clamping force estimate; represents the lead of the ball screw; represents the planetary gear main reduction ratio; represents the transmission efficiency of the planetary gear; Indicates the transmission efficiency of the ball screw.

5. The pressure sensorless control method of the electric vehicle electronic mechanical brake system according to claim 3, characterized in that: In step S23, the first clamping force estimation value is obtained by the following calculation formula: ； in, represents the first clamping force estimate; represents the magnitude of the q-axis current; represents the motor flux; represents the number of pole pairs of the motor; represents the moment of inertia; represents the time derivative of the angular velocity; represents the offset coefficient; represents a symbolic function; represents the derivative of the rotor angle with respect to time; represents the lead of the ball screw; represents the planetary gear main reduction ratio; represents the transmission efficiency of the planetary gear; Indicates the transmission efficiency of the ball screw; represents the Coulomb friction coefficient.

6. The pressure sensorless control method for the electric vehicle electronic mechanical brake system according to claim 1, characterized in that: In step S4, the optimal clamping force estimation value is obtained by the following calculation formula: ； in, represents the optimal clamping force estimation value; represents the first clamping force estimate; represents a variance of the first clamping force estimate; represents a variance of the second clamping force estimate; represents the second clamping force estimate value.

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