An eps road surface adaptive method oriented to steering motion quality

Abstract

This invention discloses an EPS road surface adaptive method for improving steering performance, comprising a load identification module, a slope identification module, a road surface adhesion coefficient identification module, and a road surface adaptive adjustment module for determining and implementing motion intensity. The load identification module uses a recursive least squares method to achieve real-time recursive estimation of the vehicle's mass based on the vehicle's longitudinal driving process. The slope identification module, based on two slope models—a constant slope model and a constant slope change rate model—accurately identifies the road slope using interactive multi-model Kalman filtering. This invention solves the problem of poor steering performance in existing electric power steering system adaptive control strategies on slippery roads, where the relationship between steering torque and vehicle motion intensity, and the return-to-center speed, do not meet driver expectations, thus improving the steering performance of vehicles on different road surfaces.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to an EPS road surface adaptive method for steering motion quality. Background Technology

[0002] In recent years, electric power steering (EPS) systems have been widely used in automobiles. As for steering, consumers are paying more attention to the driving quality of cars on different road surfaces.

[0003] Invention patent CN114291156A discloses an EPS periodic road excitation compensation method, system, and vehicle. It addresses the problem that during vehicle operation, vibrations and shaking caused by the rigid motion of the vehicle body, as well as other forms of interference such as uneven road surfaces, result in periodic noise interference in the torque signal collected by the torque sensor of the vehicle's steering wheel, causing periodic rotation of the steering wheel in a certain direction. The invention provides an EPS periodic road excitation compensation method, system, and vehicle that reduces steering wheel vibration and improves driving safety by suppressing road excitation noise. However, this control method cannot solve the problem of poor steering quality on slippery roads, where the steering quality does not meet the driver's expectations.

[0004] Invention patent CN107089261A discloses a distributed drive vehicle steering control system and method integrating EPS. It addresses the potential sideslip phenomenon that may occur when steering on split-road surfaces, based on traditional EPS system control, by incorporating additional yaw moment control to improve the handling stability of distributed drive vehicles. However, this method does not consider the vehicle's motion quality on different road surfaces; the steering feel and return-to-center speed on slippery surfaces may not meet the driver's expectations.

[0005] Chinese invention patent CN116714665A discloses a device for suppressing steering wheel vibration during high-speed vehicle operation. Addressing this issue, the device uses an adaptive torque controller to generate an adaptive torque compensation wave, which is then converted into a current signal to control the EPS motor, thus suppressing steering wheel vibration at high speeds. While this method adaptively suppresses steering wheel vibration based on vehicle speed and road surface information, it does not adaptively control the steering feel and return-to-center speed according to road conditions.

[0006] When driving on different road surfaces, the desired motion corresponding to the same steering input torque differs for the driver. On good roads, for the same steering torque, the driver often prefers a larger motion, or a smaller steering torque for the same steering motion, to reduce the handling burden and make driving easier. On wet or slippery roads, for the same steering torque, the driver usually prefers a smaller motion, or a larger steering torque for the same steering motion, to improve stability, enhance driving confidence, and ensure driving safety. Summary of the Invention

[0007] In response to the above situation, this invention adopts a different approach from the previous adaptive methods of electric power steering systems, and proposes an EPS road surface adaptive method oriented towards steering motion quality.

[0008] First, based on the vehicle's longitudinal driving process, a recursive least squares method is used to achieve real-time recursive estimation of the vehicle's mass. After establishing a constant slope model and a constant slope change rate model and determining the transfer characteristics between them, an interactive multi-model Kalman filter (IMFPDAF) is used to accurately identify the road slope. Based on the vehicle's longitudinal response and slip ratio, the road surface adhesion coefficient is identified using the adhesion coefficient curve. Finally, based on the identified road surface adhesion coefficient, the set steering style, torque hysteresis characteristics, return-to-center time characteristics, and the vehicle dynamics inverse characteristics used in the control are adjusted, thereby correcting the driver's driving intentions and improving the steering motion control accuracy.

[0009] The purpose of this invention is to solve the problem of poor steering quality and difficulty in meeting driver expectations when driving on wet and slippery roads. To address this issue, this invention proposes an EPS road surface adaptive method for improving steering quality, which adapts steering feel and self-centering performance to road conditions, thereby improving steering quality on different road surfaces.

[0010] To achieve the above objectives, the present invention provides the following technical solution:

[0011] An EPS road surface adaptive method for steering motion quality includes a load identification module, a slope identification module, a road surface adhesion coefficient identification module, and a road surface adaptive adjustment module for determining and implementing motion intensity. The specific method includes the following steps:

[0012] Step 1: Based on the longitudinal driving process of the vehicle, the recursive least squares method is used to realize the real-time recursive estimation of the vehicle mass;

[0013] Step 2: Based on the establishment of two slope models, a constant slope model and a constant slope change rate model, the road slope can be accurately identified by using interactive multi-model Kalman filtering.

[0014] Step 3: The road surface adhesion coefficient is estimated by using a road surface adhesion coefficient identification method based on vehicle longitudinal response and slip ratio using the adhesion coefficient curve.

[0015] Step 4: Based on the identified road surface adhesion coefficient, adjust the set steering style, torque hysteresis characteristics, return time characteristics, and vehicle dynamics inverse characteristics used in the control, thereby correcting the driver's driving intentions and improving the steering motion control accuracy.

[0016] As a further technical solution of the present invention: step 1 is implemented by the load identification module, as shown in equation (1):

[0017]

[0018]

[0019]

[0020] P(k=λ) -1 (1-K(k)a acc (k-1))P(k-1) (1)

[0021] In the formula: z is the calculated measurement, z = T tq i g i0η T / rF f+w (u); ε is the estimation error, and K is the least squares gain. λ represents the quality of the estimate; P is the covariance matrix; λ is the forgetting factor; k represents the current time step, and k-1 represents the previous time step.

[0022] As a further technical solution of the present invention: In step 1, the estimated value only needs to be updated when the vehicle mass is about to change significantly. The vehicle mass is about to change significantly includes two situations: I. The vehicle has just been powered on and started, at which time the number of passengers and the cargo load are unknown, and a mass estimation is required; II. The vehicle door or trunk door is opened, at which time the number of passengers and the cargo load are about to change, and a mass estimation is required.

[0023] As a further technical solution of the present invention: In step 1, when the quality estimation algorithm works for a period of time and the estimated value converges, that is, the change in the quality estimated value is less than the threshold value within a period of time, the quality estimation is stopped, and it is assumed that the vehicle quality remains unchanged at the current value.

[0024] As a further technical solution of the present invention: step 2 is implemented by the slope recognition module.

[0025] As a further technical solution of the present invention: Step 3 is implemented by the road surface adhesion coefficient identification module, specifically: a road surface adhesion coefficient identification method based on vehicle longitudinal response and slip ratio using the adhesion coefficient curve is adopted. First, the longitudinal force of the wheel is estimated, and the instantaneous adhesion coefficient and slip ratio of the wheel are calculated. On this basis, the slip ratio is judged. If the slip ratio is small, the road surface high and low adhesion are distinguished according to the slope of the μ-s curve. Otherwise, the similarity between the coefficient and slip ratio sampling points and typical road surfaces within a certain interval is calculated, and then the road surface adhesion coefficient is estimated.

[0026] As a further technical solution of the present invention: Step 4 is implemented by the road surface adaptive adjustment module for determining and realizing motion intensity, and the steering style, torque hysteresis characteristics and return time characteristics are corrected by the method shown in Equation (2);

[0027]

[0028]

[0029]

[0030]

[0031]

[0032] In the formula, These are the steering style, friction hysteresis, damping hysteresis, inertial hysteresis, and return-to-center time characteristics designed for roads with μ=1; f DS T f T d T i f RT Represents the characteristics of any road surface after modification; k DS (μ), k f (μ), k d (μ), k i (μ), k RT (μ) is a characteristic correction coefficient related to the road adhesion coefficient. All five parameters take a value of 1 when μ = 1, and k < 1 when μ < 1. DS (μ) is less than 1, while all others are greater than 1; μ is the road surface adhesion coefficient that is being identified.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. This invention solves the problem that the existing adaptive control strategy of electric power steering system has poor steering quality when driving on wet and slippery roads, and the relationship between steering torque and vehicle motion intensity and the speed of return to center do not meet the driver's expectations, thereby improving the steering quality of the vehicle when driving on different road surfaces.

[0035] 2. This invention, through the design of a load identification module, a slope identification module, a road surface adhesion coefficient identification module, and a road surface adaptive adjustment module for determining and implementing motion intensity, considers the influence of vehicle load and slope changes to identify the road surface adhesion coefficient. Based on the identification results, it adjusts the set steering style, torque hysteresis characteristics, return-to-center time characteristics, and the vehicle dynamics inverse characteristics used in control, thereby correcting the driver's motion intention and improving the accuracy of vehicle steering motion control. This makes the steering feel and return-to-center performance consistent with road conditions, significantly improving the steering motion quality when driving on different road surfaces. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the implementation scheme of the EPS road surface adaptive method for steering motion quality described in this invention.

[0037] Figure 2 This is a schematic diagram of the slope identification method based on IMMKF described in this invention.

[0038] Figure 3 This is a schematic diagram of the road surface adaptive adjustment method for determining and implementing motion intensity as described in this invention. Detailed Implementation

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0040] Reference Figure 1-3 An EPS road surface adaptive method for steering motion quality consists of a load identification module, a slope identification module, a road surface adhesion coefficient identification module, and a road surface adaptive adjustment module for determining and implementing motion intensity.

[0041] The main function of the load identification module is to achieve real-time recursive estimation of the vehicle mass based on the longitudinal driving process of the vehicle using the recursive least squares method, as shown in equation (1):

[0042]

[0043]

[0044]

[0045] P(k=λ) -1 (1-K(k)a acc (k-1))P(k-1) (1)

[0046] In the formula: z is the calculated measurement, z = T tq i g i0η T / rF f+w (u); ε is the estimation error, and K is the least squares gain. λ represents the quality of the estimate; P is the covariance matrix; λ is the forgetting factor; k represents the current time step, and k-1 represents the previous time step.

[0047] Furthermore, real-time updates to the vehicle mass estimate are not necessary in all situations. Updates are only required when the vehicle mass is likely to change significantly. For passenger vehicles, there are only two situations where the mass may change significantly: (1) when the vehicle is first powered on and started, at which point the number of passengers and cargo are unknown, requiring a mass estimate; and (2) when the vehicle doors or trunk door are opened, at which point the number of passengers and cargo may change, requiring a mass estimate. Once the mass estimation algorithm has worked for a period of time and the estimated value converges, meaning that the change in the estimated mass value over a period of time is less than the threshold value, mass estimation stops, and the vehicle mass is considered to remain unchanged at its current value.

[0048] The main function of the slope identification module is to accurately identify the road slope by using interactive multi-model Kalman filtering (IMMFPDAF) based on two slope models: a fixed slope model and a fixed slope change rate model.

[0049] The main function of the road surface adhesion coefficient identification module is to use a road surface adhesion coefficient identification method based on vehicle longitudinal response and slip ratio using the adhesion coefficient curve. First, the longitudinal force of the wheel is estimated, and the instantaneous adhesion coefficient and slip ratio of the wheel are calculated. Based on this, the slip ratio is judged. If the slip ratio is small, the slope of the μ-s curve is used to distinguish between high and low road surface adhesion. Otherwise, the similarity between the coefficient and slip ratio sampling points and typical road surfaces within a certain interval is calculated, and then the road surface adhesion coefficient is estimated.

[0050] The main function of the road surface adaptive adjustment module for determining and implementing motion intensity is to adjust the set steering style, torque hysteresis characteristics, return time characteristics, and vehicle dynamics inverse characteristics used in control based on the identified road surface adhesion coefficient, thereby correcting the driver's motion intention and improving the steering motion control accuracy.

[0051] The steering style, torque hysteresis characteristics and return-to-center time characteristics are corrected using the method shown in Equation (2).

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] In the formula, These are the steering style, friction hysteresis, damping hysteresis, inertial hysteresis, and return-to-center time characteristics designed for roads with μ=1; f DS T f T d T i f RT Represents the characteristics of any road surface after modification; k DS (μ), k f (μ), k d (μ), k i (μ), k RT (μ) is a characteristic correction coefficient related to the road adhesion coefficient. All five parameters take a value of 1 when μ = 1, and k < 1 when μ < 1. DS (μ) is less than 1, and all others are greater than 1; μ is the identified road surface adhesion coefficient. The symbol parameters are explained in Table 1 below.

[0058] Table 1: Symbol Parameter Description Table;

[0059]

[0060]

[0061] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of equivalents of the claims be included within the present invention.

[0062] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This way of describing the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment have been appropriately combined to form other embodiments that are easy for those skilled in the art to understand.

Claims

1. A steering motion quality oriented EPS road surface adaptive method, characterized by, It includes a load identification module, a slope identification module, a road surface adhesion coefficient identification module, and a road surface adaptive adjustment module for determining and implementing motion intensity. The specific method includes the following steps: Step 1: Based on the longitudinal driving process of the vehicle, the recursive least squares method is used to realize the real-time recursive estimation of the vehicle mass; Step 2: Based on the establishment of two slope models, a constant slope model and a constant slope change rate model, the road slope can be accurately identified by using interactive multi-model Kalman filtering. Step 3: The road surface adhesion coefficient is estimated by using a road surface adhesion coefficient identification method based on vehicle longitudinal response and slip ratio using the adhesion coefficient curve. Step 4: Based on the identified road adhesion coefficient, adjust the set steering style, torque hysteresis characteristics, return time characteristics, and vehicle dynamics inverse characteristics used in the control, thereby correcting the driver's intention and improving the steering motion control accuracy. Step 4 is implemented by the road surface adaptive adjustment module for determining and realizing motion intensity, and the steering style, torque hysteresis characteristics and return time characteristics are corrected by the method shown in Equation (2); （2） wherein, , , , , are the steering style, friction hysteresis, damping hysteresis, inertia hysteresis and returnability time characteristics of the road surface design, respectively; , , , , , represent the characteristics on an arbitrary road surface after correction; , , , , are the characteristic correction coefficients related to the road surface adhesion coefficient, and the five are each taken as 1 when , , is less than 1, and the others are each greater than 1; is the identified road surface adhesion coefficient.

2. The EPS road surface adaptive method for steering motion quality according to claim 1, characterized in that, Step 1 is implemented by the load identification module, as shown in equation (1): （1） In the formula: It is a measurement obtained through calculation. ; To estimate the error, It is the least squares gain. It is the estimated quality; It is the covariance matrix; It is a forgetting factor; Representing the current moment, It represents the previous moment.

3. The EPS road surface adaptive method for steering motion quality according to claim 2, characterized in that, In step 1, the estimated value only needs to be updated when the vehicle mass is about to change significantly. There are two situations where the vehicle mass is about to change significantly: Ⅰ. The vehicle has just been powered on and started, at which time the number of passengers and the cargo load are unknown, and a mass estimation is required; Ⅱ. The vehicle door or trunk door is opened, at which time the number of passengers and the cargo load are about to change, and a mass estimation is required.

4. The EPS road surface adaptive method for steering motion quality according to claim 1, characterized in that, In step 1, when the quality estimation algorithm works for a period of time and the estimated value converges, that is, when the change in the quality estimated value is less than the threshold value for a period of time, the quality estimation stops and it is assumed that the vehicle quality remains unchanged at the current value.

5. The EPS road surface adaptive method for steering motion quality according to claim 1, characterized in that, Step 2 is implemented by the slope recognition module.

6. The EPS road surface adaptive method for steering motion quality according to claim 1, characterized in that, Step 3 is implemented by the road surface adhesion coefficient identification module. Specifically, it employs a road surface adhesion coefficient identification method based on vehicle longitudinal response and slip ratio using the adhesion coefficient curve. First, it estimates the longitudinal force of the wheel and calculates the instantaneous adhesion coefficient and slip ratio of the wheel. Based on this, it judges the slip ratio. If the slip ratio is small, it determines the appropriate method based on the following criteria: The slope of the curve distinguishes between high and low adhesion of the road surface; otherwise, the road adhesion coefficient is estimated by calculating the similarity between the coefficient and slip ratio sampling points and typical road surfaces within a certain interval.

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