Comparative study of vehicle tyre–road friction coefficient estimation with a novel cost-effective method

This paper qualitatively and quantitatively reviews and compares three typical tyre–road friction coefficient estimation methods, which are the slip slope method, individual tyre force estimation method and extended Kalman filter method, and then presents a new cost-effective tyre–road friction coefficient estimation method. Based on the qualitative analysis and the numerical comparisons, it is found that all of the three typical methods can successfully estimate the tyre force and friction coefficient in most of the test conditions, but the estimation performance is compromised for some of the methods during different simulation scenarios. In addition, all of these three methods need global positioning system (GPS) to measure the absolute velocity of a vehicle. To overcome the above-mentioned problem, a novel cost-effective estimation method is proposed in this paper. This method requires only the inputs of wheel angular velocity, traction/brake torque and longitudinal acceleration, which are all easy to be measured using available sensors installed in passenger vehicles. By using this method, the vehicle absolute velocity and slip ratio can be estimated by an improved nonlinear observer without using GPS, and the friction force and tyre–road friction coefficient can be obtained from the estimated vehicle velocity and slip ratio. Simulations are used to validate the effectiveness of the proposed estimation method.     

Distributed and self-adaptive vehicle speed estimation in the composite braking case for four-wheel drive hybrid electric car

Considering the controllability and observability of the braking torques of the hub motor, Integrated Starter Generator (ISG), and hydraulic brake for four-wheel drive (4WD) hybrid electric cars, a distributed and self-adaptive vehicle speed estimation algorithm for different braking situations has been proposed by fully utilising the Electronic Stability Program (ESP) sensor signals and multiple powersource signals. Firstly, the simulation platform of a 4WD hybrid electric car was established, which integrates an electronic-hydraulic composited braking system model and its control strategy, a nonlinear seven degrees-of-freedom vehicle dynamics model, and the Burckhardt tyre model. Secondly, combining the braking torque signals with the ESP signals, self-adaptive unscented Kalman sub-filter and main-filter adaptable to the observation noise were, respectively, designed. Thirdly, the fusion rules for the sub-filters and master filter were proposed herein, and the estimation results were compared with the simulated value of a real vehicle speed. Finally, based on the hardware in-the-loop platform and by picking up the regenerative motor torque signals and wheel cylinder pressure signals, the proposed speed estimation algorithm was tested under the case of moderate braking on the highly adhesive road, and the case of Antilock Braking System (ABS) action on the slippery road, as well as the case of ABS action on the icy road. Test results show that the presented vehicle speed estimation algorithm has not only a high precision but also a strong adaptability in the composite braking case.     

A real-time approach to robust identification of tyre–road friction characteristics on mixed-μ roads

ABSTRACT

The interaction between the tyre and the road is crucial for understanding the dynamic behaviour of a vehicle. The road–tyre friction characteristics play a key role in the design of braking, traction and stability control systems. Thus, in order to have a good performance of vehicle dynamic stability control, real-time estimation of the tyre–road friction coefficient is required. This paper presents a new development of an on-line tyre–road friction parameters estimation methodology and its implementation using both LuGre and Burckhardt tyre–road friction models. The proposed method provides the capability to observe the tyre–road friction coefficient directly using measurable signals in real-time. In the first step of our approach, the recursive least squares is employed to identify the linear parameterisation form of the Burckhardt model. The identified parameters provide, through a T–S fuzzy system, the initial values for the LuGre model. Then, a new LuGre model-based nonlinear least squares parameter estimation algorithm using the proposed static form of the LuGre to obtain the parameters of LuGre model based on recursive nonlinear optimisation of the curve fitting errors is presented. The effectiveness and performance of the algorithm are demonstrated through the real-time model simulations with different longitudinal speeds and different kinds of tyres on various road surface conditions in both Matlab/Carsim environments as well as collected data from real experiments on a commercial trailer.     

Longitudinal wheel slip during ABS braking

Anti-lock braking system (ABS) braking tests with two subcompact passenger cars were performed on dry and wet asphalt, as well as on snow and ice surfaces. The operating conditions of the tyres in terms of wheel slip were evaluated using histograms of the wheel slip data. The results showed different average slip levels for different road surfaces. It was also found that changes in the tyre tread stiffness affected the slip operating range through a modification of the slip value at which the maximum longitudinal force is achieved. Variation of the tyre footprint length through modifications in the inflation pressure affected the slip operating range as well. Differences in the slip distribution between vehicles with different brake controllers were also observed. The changes in slip operating range in turn modified the relative local sliding speeds between the tyre and the road. The results highlight the importance of the ABS controller's ability to adapt to changing slip–force characteristics of tyres and provide estimates of the magnitude of the effects of different tyre and road operating conditions.     

Cooperative control of the motor and the electric booster brake to improve the stability of an in-wheel electric vehicle

A cooperative control algorithm for an in-wheel motor and an electric booster brake is proposed to improve the stability of an in-wheel electric vehicle. The in-wheel system was modeled by dividing it into motor and mechanical parts, and the electric booster brake was modeled through tests. In addition, the response characteristics of the in-wheel system and the electric booster brake were compared through a frequency response analysis. In the cooperative control, the road friction coefficient was estimated using the wheel speed, motor torque, and braking torque of each wheel, and the torque limit of the wheel to the road was determined using the estimated road friction coefficient. Based on the estimated road friction coefficient and torque limit, a cooperative algorithm to control the motor and the electric booster brake was proposed to improve the stability of the in-wheel electric vehicle. The performance of the proposed cooperative control algorithm was evaluated through a hardware-in-the-loop simulation (HILS). Furthermore, to verify the performance of the proposed cooperative control algorithm, a test environment was constructed for the anti-lock braking system (ABS) hydraulic module hardware, and the performance of the cooperative control algorithm was compared with that of the ABS by means of a HILS test.     

Robust road friction estimation during vehicle steering

Automated vehicles require information on the current road condition, i.e. the tyre–road friction coefficient for trajectory planning, braking or steering interventions. In this work, we propose a framework to estimate the road friction coefficient with stability and robustness guarantee using total aligning torque in vehicle front axle during steering. We first adopt a novel strategy to estimate the front axle lateral force which performs better than the classical unknown input observer. Then, combined with an indirect measurement based on estimated total aligning torque and front axle lateral force, a non-linear adaptive observer is designed to estimate road friction coefficient with stability guarantee. To increase the robustness of the estimation result, criteria are proposed to decide when to update the estimated road conditions. Simulations and experiments under various road conditions validate the proposed framework and demonstrate its advantage in stability by comparing it with the method utilising the wide-spread Extended Kalman Filter.     

Coordinated vehicle traction control based on engine torque and brake pressure under complicated road conditions

Vehicle traction control system has been developed to enhance the traction capability and the direction stability of the driving wheels through the tyre slip ratio regulation. Under normal situations, if the tyre slip ratio exceeds a certain threshold, the slip ratio of the driving wheel is regulated by the coupled interaction of the engine torque and the active brake pressure. In order to obtain the best driving performance on a road under complicated friction conditions, the driving torque and the active brake pressure, need to be decoupled and adjusted to avoid penalisation of each other. In this paper, a coordinated cascade control method with two sliding-mode variable structure controllers is presented. In this control method, the driving wheel slip ratio is regulated by adjusting the engine torque and the wheel brake pressure. Through the sliding-mode controller, the engine torque is tuned to achieve the maximum driving acceleration and then the active brake pressure is applied to the slipped wheel for further modification of the wheel slip ratio. The advantage of this control method is that through proper regulation, the conflict between the two control inputs could be avoided. Finally, the simulation results validate the effectiveness of the proposed method.     

Slip-Angle Estimation for Vehicle Stability Control

Recently, some direct yaw-moment control systems have been in development. Obviously, such systems need accurate slip-angle information. This paper describes a strategy of vehicle slip angle estimation. The difficulty in slip angle estimation is due to nonlinear characteristics of tyres and influence of relative slant of the road surface. To solve this difficulty, a combined method of model observer and direct integration method is proposed. In this method, two kinds of values of the side forces of the wheels are provided, i.e., direct detected values by the G-sensor and values from a tyre model. Then those values are combined appropriately which results in the combination of model observer and direct integration. A feedback algorithm, redesigned to suppress the influence of tyre model error, is applied in the observer. Considering interference of road surface and its avoidance, road slant angle is estimated and consequently vehicle model is corrected. The estimated value of the road friction coefficient is given by the acceleration, and an adequate bias, depending on yaw-deviation, is added. The calculation method of reference yaw-velocity is improved, in order to avoid interference of road slant and variation of dynamic characteristic of vehicle.     

Slip-Angle Estimation for Vehicle Stability Control

Recently, some direct yaw-moment control systems have been in development. Obviously, such systems need accurate slip-angle information. This paper describes a strategy of vehicle slip angle estimation. The difficulty in slip angle estimation is due to nonlinear characteristics of tyres and influence of relative slant of the road surface. To solve this difficulty, a combined method of model observer and direct integration method is proposed. In this method, two kinds of values of the side forces of the wheels are provided, i.e., direct detected values by the G-sensor and values from a tyre model. Then those values are combined appropriately which results in the combination of model observer and direct integration. A feedback algorithm, redesigned to suppress the influence of tyre model error, is applied in the observer. Considering interference of road surface and its avoidance, road slant angle is estimated and consequently vehicle model is corrected. The estimated value of the road friction coefficient is given by the acceleration, and an adequate bias, depending on yaw-deviation, is added. The calculation method of reference yaw-velocity is improved, in order to avoid interference of road slant and variation of dynamic characteristic of vehicle.     

汽车防抱死制动系统的自抗扰控制研究

汽车防抱死制动系统(Anti-lock Braking System,ABS)的作用是确保汽车制动时行驶方向的稳定性、可靠性,但是目前仍存在非线性、时变性以及参数不确定性等问题.为保证汽车制动行驶过程中的操纵稳定性和安全性,进一步实现各工况下防抱死制动系统的优化控制,以影响整车稳定的变量滑移率为研究对象,分析所设计策略...     

Experimental investigations on continuous regenerative anti-lock braking system of full electric vehicle

Functions of anti-lock braking for full electric vehicles (EV) with individually controlled wheel drive can be realized through conventional brake system actuating friction brakes and regenerative brake system actuating electric motors. To analyze advantages and limitations of both variants of anti-lock braking systems (ABS), the presented study introduces results of experimental investigations obtained from proving ground tests of all-wheel drive EV. The brake performance is assessed for three different configurations: hydraulic ABS; regenerative ABS only on the front axle; blended hydraulic and regenerative ABS on the front axle and hydraulic ABS on the rear axle. The hydraulic ABS is based on a rule-based controller, and the continuous regenerative ABS uses the gain-scheduled proportional-integral direct slip control with feedforward and feedback control parts. The results of tests on low-friction road surface demonstrated that all the ABS configurations guarantee considerable reduction of the brake distance compared to the vehicle without ABS. In addition, braking manoeuvres with the regenerative ABS are characterized by accurate tracking of the reference wheel slip that results in less oscillatory time profile of the vehicle deceleration and, as consequence, in better driving comfort. The results of the presented experimental investigations can be used in the process of selection of ABS architecture for upcoming generations of full electric vehicles with individual wheel drive.     

Estimation of the tyre–road maximum friction coefficient and slip slope based on a novel tyre model

In this article, a new approach to estimate the vehicle tyre forces, tyre–road maximum friction coefficient, and slip slope is presented. Contrary to the majority of the previous work on this subject, a new tyre model for the estimation of the tyre–road interface characterisation is proposed. First, the tyre model is built and compared with those of Pacejka, Dugoff, and one other tyre model. Then, based on a vehicle model that uses four degrees of freedom, an extended Kalman filter (EKF) method is designed to estimate the vehicle motion and tyre forces. The shortcomings of force estimation are discussed in this article. Based on the proposed tyre model and the improved force measurements, another EKF is implemented to estimate the tyre model parameters, including the maximum friction coefficient, slip slope, etc. The tyre forces are accurately obtained simultaneously. Finally, very promising results have been achieved for pure acceleration/braking for varying road conditions, both in pure steering and combined manoeuvre simulations.     

Estimation of longitudinal speed robust to road conditions for ground vehicles

This article seeks to develop a longitudinal vehicle velocity estimator robust to road conditions by employing a tyre model at each corner. Combining the lumped LuGre tyre model and the vehicle kinematics, the tyres internal deflection state is used to gain an accurate estimation. Conventional kinematic-based velocity estimators use acceleration measurements, without correction with the tyre forces. However, this results in inaccurate velocity estimation because of sensor uncertainties which should be handled with another measurement such as tyre forces that depend on unknown road friction. The new Kalman-based observer in this paper addresses this issue by considering tyre nonlinearities with a minimum number of required tyre parameters and the road condition as uncertainty. Longitudinal forces obtained by the unscented Kalman filter on the wheel dynamics is employed as an observation for the Kalman-based velocity estimator at each corner. The stability of the proposed time-varying estimator is investigated and its performance is examined experimentally in several tests and on different road surface frictions. Road experiments and simulation results show the accuracy and robustness of the proposed approach in estimating longitudinal speed for ground vehicles.     

Emergency Braking Control with an Observer-based Dynamic Tire/Road Friction Model and Wheel Angular Velocity Measurement

Summary A control scheme for emergency braking of vehicles is designed. The tire/road friction is described by a LuGre dynamic friction model. The control system output is the pressure in the master cylinder of the brake system. The controller utilizes estimated states for a feedback control law that achieves a near maximum deceleration. The state observer is designed using linear matrix inequality (LMI) techniques. The analysis shows that using the wheel angular speed information exclusively is not sufficient to rapidly estimate the velocity and relative velocity, due to the fact that the dynamical system is almost unobservable with this measurement as output. Findings are confirmed by simulation results that show that the estimated vehicle velocity and relative velocity converge slowly to their true values, even though the internal friction state and friction parameters converge quickly. The proposed control system has two main advantages when compared with an antilock braking system (ABS): (1) it produces a source of a priori information regarding safe spacing between vehicles that can be used to increase safety levels in the highway; and (2) it achieves a near optimal braking strategy with less chattering.     

Emergency Braking Control with an Observer-based Dynamic Tire/Road Friction Model and Wheel Angular Velocity Measurement

Summary A control scheme for emergency braking of vehicles is designed. The tire/road friction is described by a LuGre dynamic friction model. The control system output is the pressure in the master cylinder of the brake system. The controller utilizes estimated states for a feedback control law that achieves a near maximum deceleration. The state observer is designed using linear matrix inequality (LMI) techniques. The analysis shows that using the wheel angular speed information exclusively is not sufficient to rapidly estimate the velocity and relative velocity, due to the fact that the dynamical system is almost unobservable with this measurement as output. Findings are confirmed by simulation results that show that the estimated vehicle velocity and relative velocity converge slowly to their true values, even though the internal friction state and friction parameters converge quickly. The proposed control system has two main advantages when compared with an antilock braking system (ABS): (1) it produces a source of a priori information regarding safe spacing between vehicles that can be used to increase safety levels in the highway; and (2) it achieves a near optimal braking strategy with less chattering.     

Identifying tyre models directly from vehicle test data using an extended Kalman filter

Individual tyre models are traditionally derived from component tests, with their parameters matched to force and slip measurements. They are imported into vehicle models which should, but do not always properly provide suspension geometry interaction. Recent advances in Global Positioning System (GPS)/inertia vehicle instrumentation now make full state measurement viable in test vehicles, so tyre slip behaviour is directly measurable. This paper uses an extended Kalman filter for system identification, to derive individual load-dependent tyre models directly from these test vehicle state measurements. The resulting model therefore implicitly compensates for suspension geometry and compliance. The paper looks at two variants of the tyre model, and also considers real-time adaptation of the model to road surface friction variations. Test vehicle results are used exclusively, and the results show successful tyre model identification, improved vehicle model state prediction – particularly in lateral velocity reproduction – and an effective real-time solution for road friction estimation.     

Nonlinear tire-road friction control based on tire model parameter identification

A hierarchical control structure is a more suitable structural scheme for integrated chassis control. Generally, this type of structure has two main functions. The upper layer manages global control and force allocation, while the bottom layer allocates realized forces with 4 independent local tire controllers. The way to properly allocate these target forces poses a difficult task for the bottom layer. There are two key problems that require attention: obtaining the nonlinear time-varying coefficient of friction between the tire and different road surfaces and accurately tracking the desired forces from the upper layer. This paper mainly focuses on longitudinal tire-road friction allocation and control strategies that are based on the antilock braking system (ABS). Although it is difficult to precisely measure longitudinal tire-road friction forces for frequently changing road surface conditions, they can be estimated with a real-time measurement of brake force and angular acceleration at the wheels. The Magic Formula model is proposed as the reference model, and its key parameters are identified online using a constrained hybrid genetic algorithm to describe the evolution of tire-road friction with respect to the wheel slip. The desired wheel slip, with respect to the reference tire-road friction force from the top layer, is estimated with the inverse quadratic interpolation method. The tire-road friction controller of the extended anti-lock braking system (Ext-ABS) is designed through use of the nonlinear sliding mode control method. Simulation results indicate that acceptable modifications to changes in road surface conditions and adequate stability can be expected from the proposed control strategy.     

Wheel slip control with torque blending using linear and nonlinear model predictive control

Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.     

Design of tyre force excitation for tyre–road friction estimation

Knowledge of the current tyre–road friction coefficient is essential for future autonomous vehicles. The environmental conditions, and the tyre–road friction in particular, determine both the braking distance and the maximum cornering velocity and thus set the boundaries for the vehicle. Tyre–road friction is difficult to estimate during normal driving due to low levels of tyre force excitation. This problem can be solved by using active tyre force excitation. A torque is added to one or several wheels in the purpose of estimating the tyre–road friction coefficient. Active tyre force excitation provides the opportunity to design the tyre force excitation freely. This study investigates how the tyre force should be applied to minimise the error of the tyre–road friction estimate. The performance of different excitation strategies was found to be dependent on both tyre model choice and noise level. Furthermore, the advantage with using tyre models with more parameters decreased when noise was added to the force and slip ratio.