Approach to estimation of vehicle-road longitudinal friction coefficient

According to the road adaptive requirements for the vehicle longitudinal safety assistant system an estimation method of the road longitudinal friction coefficient is proposed.The method can simultaneously be applied to both the high and the low slip ratio conditions. Based on the simplified magic formula tire model the road longitudinal friction coefficient is preliminarily estimated by the recursive least squares method.The estimated friction coefficient and the tires model parameters are considered as extended states. The extended Kalman filter algorithm is employed to filter out the noise and adaptively adjust the tire model parameters. Then the final road longitudinal friction coefficient is accurately and robustly estimated. The Carsim simulation results show that the proposed method is better than the conventional algorithm. The road longitudinal friction coefficient can be quickly and accurately estimated under both the high and the low slip ratio conditions.The error is less than 0.1 and the response time is less than 2 s which meets the requirements of the vehicle longitudinal safety assistant system.

Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

The accurate estimation of road friction coeffi- cient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coef- ficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coef- ficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode sur- face. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels. The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time andresist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate.

Identification of Maximum Road Friction Coefficient and Optimal Slip Ratio Based on Road Type Recognition

The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.

Tire Road Friction Coefficient Estimation:Review and Research Perspectives

Many surveys on vehicle traffic safety have shown that the tire road friction coefficient(TRFC)is correlated with the probability of an accident.The probability of road accidents increases sharply on slippery road surfaces.Therefore,accurate knowledge of TRFC contributes to the optimization of driver maneuvers for further improving the safety of intelligent vehicles.A large number of researchers have employed different tools and proposed different algorithms to obtain TRFC.This work investigates these different methods that have been widely utilized to estimate TRFC.These methods are divided into three main categories:off-board sensors-based,vehicle dynamics-based,and data-driven-based methods.This review provides a comparative analysis of these methods and describes their strengths and weaknesses.Moreover,some future research directions regarding TRFC estimation are presented.

Uphillshift decision strategy of an AMT off-road vehicle based on generalized road resistance coefficient

In order to improve the shift decision strategy for an off-road vehicle with automated manual transmission（AMT）,the generalized road resistance coefficient is defined based on the longitudinal dynamics analysis.Vehicle mass and generalized road resistance coefficient are estimated using the recursive least square（RLS）method with multiple forgetting factors.The improved shift schedule is designed based on the generalized road resistance coefficient under uphill road condition.The simulation and real vehicle test verify the effectiveness of improved shift strategy and the improvement of vehicle dynamic performance.

Road Friction Coefficient Real-Time Identification Based on the Tire Dynamic Friction Model

Road friction coefficient real-time estimation methods is an important issue and problem in automotive active safety con- trol system development. First a fixed feedback gain sliding mode observer of road adhesion coefficient is designed through the es-tablishment of tire/road dynamic friction model in this article. The simulation results shows that the observer can well real-time iden-tify the current road adhesion characteristics. And more importantly, the observer only need wheel speed signal and the braking torque （brake pressure） signal, so the system is low cost, and its adaptability is good. There is no doubt this estimation method has a good application prospect.

Mathematical Models of Tire-Lateral Road Adhesion for Use in Road Vehicle Dynamics Studies

Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad adhesion revolutionize the Pacejka's model in concept and therefore make it possible for applications in vehicle dynamics studies by the expression of lateral adhesion coefficient as a function of wheel slip ratio,instead of the wheel slip angle,taking into account in the mean time the influences of mad surface condition, vehicle velocity,vertical load,tire slip angle,and wheel camber angle.

Dual Extended Kalman Filter for Combined Estimation of Vehicle State and Road Friction

Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, many estimation methods have been put forward to solve such problems, in which Kalman filter becomes one of the most popular techniques. Nevertheless, the use of complicated model always leads to poor real-time estimation while the role of road friction coefficient is often ignored. For the purpose of enhancing the real time performance of the algorithm and pursuing precise estimation of vehicle states, a model-based estimator is proposed to conduct combined estimation of vehicle states and road friction coefficients. The estimator is designed based on a three-DOF vehicle model coupled with the Highway Safety Research Institute（HSRI） tire model; the dual extended Kalman filter （DEKF） technique is employed, which can be regarded as two extended Kalman filters operating and communicating simultaneously. Effectiveness of the estimation is firstly examined by comparing the outputs of the estimator with the responses of the vehicle model in CarSim under three typical road adhesion conditions（high-friction, low-friction, and joint-friction）. On this basis, driving simulator experiments are carried out to further investigate the practical application of the estimator. Numerical results from CarSim and driving simulator both demonstrate that the estimator designed is capable of estimating the vehicle states and road friction coefficient with reasonable accuracy. The DEKF-based estimator proposed provides the essential information for the vehicle active control system with low expense and decent precision, and offers the possibility of real car application in future.

Road Friction Estimation under Complicated Maneuver Conditions for Active Yaw Control

Road friction coefficient is a key factor for the stability control of the vehicle dynamics in the critical conditions. Obviously the vehicle dynamics stability control systems, including the anti-lock brake system（ABS）, the traction control system（TCS）, and the active yaw control（AYC） system, need the accurate tire and road friction information. However, the simplified method based on the linear tire and vehicle model could not obtain the accurate road friction coefficient for the complicated maneuver of the vehicle. Because the active braking control mode of AYC is different from that of ABS, the road friction coefficient cannot be estimated only with the dynamics states of the tire. With the related dynamics states measured by the sensors of AYC, a comprehensive strategy of the road friction estimation for the active yaw control is brought forward with the sensor fusion technique. Firstly, the variations of the dynamics characteristics of vehicle and tire, and the stability control mode in the steering process are considered, and then the proper road friction estimation methods are brought forward according to the vehicle maneuver process. In the steering maneuver without braking, the comprehensive road friction from the four wheels may be estimated based on the multi-sensor signal fusion method. The estimated values of the road friction reflect the road friction characteristic. When the active brake involved, the road friction coefficient of the braked wheel may be estimated based on the brake pressure and tire forces, the estimated values reflect the road friction between the braked wheel and the road. So the optimal control of the wheel slip rate may be obtained according to the road friction coefficient. The methods proposed in the paper are integrated into the real time controller of AYC, which is matched onto the test vehicle. The ground tests validate the accuracy of the proposed method under the complicated maneuver conditions.

Modeling and analytical calculation of road damage coefficient considering tire pressure and damping of vehicles

The road damage coefficientβis a significant indicator to estimate the degree of the road damage caused by vehicles.The existing calculation method ofβis not convenient for the engineering application.To effectively evaluate the damage degree and facilitate the engineering application,this paper studied the simple and reliable analytical calculation method ofβ.Firstly,a dynamic model of the vehicle–road system was created.The tire pressure and the tire damping were considered in the model.Moreover,the relationship between the tire vertical stiffness and the tire pressure is approximated as a linear function.Secondly,based on the dynamic model,according to the definition ofβ,a concise analytical formula ofβwas derived and verified by numerical simulations.The relative errors of the analytical calculation results are all less than 0.1%.Thirdly,the influences of the tire pressure p,the damping ratioξs of the suspension system,and the damping ratioξt of the wheel system onβwere analyzed.Moreover,based on the analytical formula ofβ,a mathematical model of the optimal damping matching for the suspension system was established and a case study was also given.The research results show that the larger the tire pressure p,the larger the value ofβis.For each p,there is an optimal damping ratioξs.If the tire damping is ignored,it will lead to the design error forξs.Finally,some important conclusions were drawn.The analytical formula ofβand the conclusions can provide valuable references for the analysis of the road damage and the initial design of vehicle suspensions.