Tire-road Adhesion Research Articles

Vehicle Lateral Control Based on Dynamic Boundary of Phase Plane Based on Tire Characteristics

Lateral control is an essential safety control technology for autonomous vehicles, but the effectiveness of lateral control technology relies heavily on the precision of vehicle motion state judgements. In order to achieve accurate judgements of the vehicle motion state and to improve the control effectiveness of vehicle maneuverability and the stability controller, this paper starts with an analysis of phase plane stability. A simulation analysis is conducted to investigate the effect of the vehicle steering angle of the front wheels, the longitudinal velocity, and the tire–road adhesion coefficient on the boundary of the stability area. The stable area of the phase plane was partitioned using the proposed novel quadrilateral method, and we established a stability area regression model using machine learning methods. We analyzed the inherent connection between the lateral tire forces and the principles of vehicle maneuverability and stability control, indirectly combining the characteristics of tire forces with vehicle maneuverability and stability control. An allocation algorithm for maneuverability and stability control was designed. A co-simulation indicates that the vehicle stability controller not only accurately assesses the motion state of the vehicle but also demonstrates a considerably better performance in maneuverability and stability control compared to a controller using the traditional partitioning method of stable regions. The suggested allocation method enhances vehicle maneuverability and stability by enabling a seamless transition between the two and improving the effectiveness of stability control.

Pacejka-Like Curve-Based Speed Reference Generators for Electric Vehicles Powered by in-Wheel Motors

Recently, motor speed reference generators have been designed for the cruise control of electric vehicles with either centralized electric motors (straight manoeuvres) or in-wheel motors (bend manoeuvres with sufficiently small constant steering angles). Steady-state operation at a safe (though conservative) tire longitudinal slip can be achieved, with no a priori knowledge regarding the occurrence of a specific external condition. Here, an innovative solution is presented. It is based on an ingenious use of Pacejka-like curves – representing the torque current-slip characteristics of the vehicle – to design a new contraction-mapping-based automatic tuning procedure for the longitudinal velocity of the vehicle. Such an innovative procedure overcomes the highly conservative nature of the previous approach in terms of unduly small longitudinal velocities (and yaw rates) under relatively favourable external conditions while guaranteeing a safe operating condition close to the maximum of the torque-slip characteristics with no knowledge of the tire-road adhesion coefficient. Comparative CarSim simulations illustrate the effectiveness of the proposed approach, in the presence of uncertain parameters and complex vehicle dynamics that are neglected at the control design stage.

Improved Technique for Autonomous Vehicle Motion Planning Based on Integral Constraints and Sequential Optimization

The study is dedicated to elaborating and analyzing a technique for autonomous vehicle (AV) motion planning based on sequential trajectory and kinematics optimization. The proposed approach combines the finite element method (FEM) basics and nonlinear optimization with nonlinear constraints. There were five main innovative aspects introduced in the study. First, a 7-degree polynomial was used to improve the continuity of piecewise functions representing the motion curves, providing 4 degrees of freedom (DOF) in a node. This approach allows using the irregular grid for roadway segments, increasing spans where the curvature changes slightly, and reducing steps in the vicinity of the significant inflections of motion boundaries. Therefore, the segment length depends on such factors as static and moving obstacles, average road section curvature, camera sight distance, and road conditions (adhesion). Second, since the method implies splitting the optimization stages, a strategy for bypassing the moving obstacles out of direct time dependency was developed. Thus, the permissible area for maneuvering was determined using criteria of safety distance between vehicles and physical limitation of tire–road adhesion. Third, the nodal inequality constraints were replaced by the nonlinear integral equality constraints. In contrast to the generally distributed approach of restricting the planning parameters in nodes, the technique of integral equality constraints ensures the disposition of motion parameters’ curves strictly within the preset boundaries, which is especially important for quite long segments. In this way, the reliability and stability of predicted parameters are improved. Fourth, the seamless continuity of both the sought parameters and their derivatives is ensured in transitional nodes between the planning phases and adjacent global coordinate systems. Finally, the problem of optimization rapidity to match real-time operation requirements was addressed. For this, the quadrature integration approach was implemented to represent and keep all the parameters in numerical form. The study considered cost functions, limitations stipulated by the vehicle kinematics and dynamics, as well as initial and transient conditions between the planning stages. Simulation examples of the predicted trajectories and curves of kinematic parameters are demonstrated. The advantages and limitations of the proposed approach are highlighted.

Stability control based on three-dimensional portraits for four-wheel-independent-drive EV

In this paper, a two-stage expectation stability controller was proposed for driving stability of four wheel independent drive electric vehicles. The proposed controller has three levels. There were three steps to the stability control of the vehicle. First, the three-dimensional state portraits were drawn based on the 14DOFs vehicle model and used the s tem equation to find two-stage expectation. The surface was derived from the analysis of the tire-road adhesion divides the portraits into safe areas and unsafe areas. Second, the stability controller with sliding mode algorithm was designed. When the state parameter is in the unsafe areas, the safe boundary surface is taken as the first-stage expectation; after the system enters the safe areas, the stem is taken as the second-stage expectation. Then the fuzzy algorithm is applied to distribute the control demand of yaw moment to generate the torques of each in-wheel motor. Finally, simulation verification is performed in Simulink-CarSim co-simulation environment. The simulation results show that the designed control strategy can improve the lateral stability while the loss of longitudinal speed is within 3.25%.

Multi-Objective Optimization Study of Regenerative Braking Control Strategy for Range-Extended Electric Vehicle

Currently, the researches on the regenerative braking system (RBS) of the range-extended electric vehicle (R-EEV) are inadequate, especially on the comparison and analysis of the multi-objective optimization (MOO) problem. Actually, the results of the MOO problem should be mutually independent and balanced. With the aim of guaranteeing comprehensive regenerative braking performance (CRBP), a revised regenerative braking control strategy (RRBCS) is introduced, and a method of the MOO algorithm for RRBCS is proposed to balance the braking performance (BP), regenerative braking loss efficiency (RBLE), and battery capacity loss rate (BCLR). Firstly, the models of the main components related to the RBS of the R-EEV for the calculation of optimization objectives are built in MATLAB/Simulink and AVL/Cruise. The BP, RBLE, and BCLR are selected as the optimization objectives. The non-dominated sorting genetic algorithm (NSGA-II) is applied in RRBCS to solve the MOO problem, and a group of the non-inferior Pareto solution sets are obtained. The simulation results show a clear conflict that three optimization objectives cannot be optimal at the same time. Then, we evaluate the performance of the proposed method by taking the individual with the optimal CRBP as the final optimal solution. The comparation among BP, RBLE, BCLR, and CRBP before and after optimization are analyzed and discussed. The results illustrate that characteristic parameters of RRBCS is crucial to optimization objectives. After parameters optimization, regenerative braking torque works early to increase braking energy recovery on low tire-road adhesion condition, and to reduce the battery capacity loss rate at the expense of small braking energy recovery on the medium tire-road adhesion condition. In addition, the results of the sensitivity analysis show that after parameter optimization, RRBCS is proved to perform better road adaptability regarding the distribution of solutions. These results thoroughly validate the proposed approach for multi-objective optimization of RRBCS and have a strong directive to optimize the control strategy parameters of RBS.

Vehicle Stability Control Strategy Based on Recognition of Driver Turning Intention for Dual-Motor Drive Electric Vehicle

Vehicle stability control should accurately interpret the driving intention and ensure that the actual state of the vehicle is as consistent as possible with the desired state. This paper proposes a vehicle stability control strategy, which is based on recognition of the driver’s turning intention, for a dual-motor drive electric vehicle. A hybrid model consisting of Gaussian mixture hidden Markov (GHMM) and Generalized Growing and Pruning RBF (GGAP-RBF) neural network is constructed to recognize the driver turning intention in real time. The turning urgency coefficient, which is computed on the basis of the recognition results, is used to establish a modified reference model for vehicle stability control. Then, the upper controller of the vehicle stability control system is constructed using the linear model predictive control theory. The minimum of the quadratic sum of the working load rate of the vehicle tire is taken as the optimization objective. The tire-road adhesion condition, performance of the motor and braking system, and state of the motor are taken as constraints. In addition, a lower controller is established for the vehicle stability control system, with the task of optimizing the allocation of additional yaw moment. Finally, vehicle tests were carried out by conducting double-lane change and single-lane change experiments on a platform for dual-motor drive electric vehicles by using the virtual controller of the A&D5435 hardware. The results show that the stability control system functions appropriately using this control strategy and effectively improves the stability of the vehicle.

Nonlinear Robust Control of Antilock Braking Systems Assisted by Active Suspensions for Automobile

In this brief, a novel robust control of an antilock braking system (ABS) with the assistance of an active suspension system (ASS) is proposed for automobile to improve the braking performance. Different from other ABS, not the reference wheel slip ratio but the peak tire–road adhesion coefficient is taken as the control object, and the barrier Lyapunov function control method is adopted to confine the control object within a smaller and more stable area. Besides, the rolling resistance is taken as an external disturbance and counteracted by a modified controller. Furthermore, the increase of a tire vertical load via the ASS is explored to further shorten the braking distance under the condition that the trajectory of the sprung mass and suspension space is bounded to a predetermined limitation. Finally, a favorable control simulation consequence is obtained, validating the effectiveness of the proposed control scheme.

Performance Analysis of the Sliding Mode Control for Automated Vehicle Path Tracking at Low Adhesion Surfaces

The article analyses prospects of using a type of robust controllers called relay regulators for automation of vehicle lateral motion. The operation of these regulators in so-called sliding modes is considered along with the “chattering” problem caused by deviations from the “ideal” sliding mode inevitable in actual implementations. For the analysis of vehicle motion, a mathematical model was elaborated, which calculates vehicle dynamics taking into account non-linear tire-road adhesion characteristics. In the conducted study, emphasis was put on low adhesion surfaces, which can be considered as the most difficult case for automatic lateral control of a vehicle. In order to implement automated path tracking within the model, two relay regulators were elaborated differing from one another in the order of dynamics. A comparative study of these regulators was conducted by means of simulations. The regulator that had shown best performance was then tested for robustness by means of modeling, in which maneuvers on snow, ice and a mixed surface were simulated.

Optimized Handling Stability Control Strategy for a Four In-Wheel Motor Independent-Drive Electric Vehicle

An optimized handling stability control strategy is put forward aiming at enhancing a four in-wheel independent-drive motors electric vehicle (4WIDEV) performance capable of handling and stability. The optimized control strategy is designed by a hierarchical control structure, which mainly includes vehicle motion controller and vehicle torque distribution controller. Lateral stability controller, in-vehicle motion controller, which yields the generalized force and generalized yaw moment required of the vehicle, is designed into two modes: an instability control mode and a continuous control mode, which mode is activated determining by stability judgment controller based on phase portraits of sideslip angle and yaw rate. When the vehicle state exceeds the stability envelope region, instability control mode based on envelope control is utilized by sliding mode control method, simultaneously controlling the two-vehicle states variables, whereas continuous control mode is performed with adaptive adjustment of the weight parameter according to pre-defined stability degree. The lateral stability controller with adaptive switching two modes exhibits excellent handling stability performance under normal driving conditions, especially under critical conditions, such as on low tire-road adhesion coefficient. The vehicle torque distribution controller assigns driving or regenerative braking torque to four wheels reasonably and efficiently to satisfy the generalized force and the generalize yaw moment acquired by the vehicle motion controller, which synchronously considers the motor output capability and tire friction ellipse constraints while maintains each wheel slip ratio within the stable range. The results in co-simulation experiments based on Carsim and MATLAB/Simulink verify the proposed control strategy, compared with other control strategies, and demonstrate the effective improvement 4WIDEV’s performance in terms of handling stability especially under critical conditions.

A novel control strategy of regenerative braking system for electric vehicles under safety critical driving situations

This paper mainly focuses on control strategy of the regenerative braking system of an electric vehicle under safety critical driving situations. With the aims of guaranteeing the electric vehicle stability in various types of tire-road adhesion conditions, based on the characteristics of an electrified powertrain, a novel control strategy of regenerative braking system is proposed for electric vehicles during anti-lock braking procedures. Firstly, the main construction of the case-study electric car with regenerative braking system is introduced. Next, based on the phase plane theory, the optimal brake torque is calculated for ABS control of an electric vehicle. Then, an allocation control, wherein the required optimal brake torque is divided into two parts that are disposed respectively by the friction and regenerative brakes, is discussed. In addition, two parameters for evaluating regeneration braking energy efficiency contribution while in the deceleration braking process are defined. Furthermore, a novel regenerative braking control strategy named “serial control strategy” is proposed. Finally, the road tests are implemented in four types of tire-road adhesion conditions under safety-critical driving situations. The test results validate the effectiveness and feasibility of the proposed control strategy.

Acceleration Slip Regulation for Four-Wheel-Independently-Actuated Electric Vehicles Based on Road Identification through the Fuzzy Logic

In this paper, a novel method is proposed for tire-road adhesion coefficient estimation based on the fuzzy logic theory for a four-wheel-independently-actuated electric vehicle (FWIA EV). In the meantime, the vehicle velocity is estimated by the unscented Kalman filter method, which provides the foundation for real-time slip ratio calculation. A PID controller is further synthesized for Acceleration Slip Regulation (ASR) to derive the output torque of each in-wheel motor through feeding the error between the real-time slip ratio and the optimal slip ratio based on road identification. Finally, the effectiveness of the proposed scheme is validated under opposite roads with full acceleration in simulation, and the results show that the proposed ASR scheme is capable of improving the driving performance of the FWIA EV.

Model predictive control-based efficient energy recovery control strategy for regenerative braking system of hybrid electric bus

As one of the main working modes, the energy recovered with regenerative braking system provides an effective approach so as to greatly improve fuel economy of hybrid electric bus. However, it is still a challenging issue to ensure braking stability while maximizing braking energy recovery. To solve this problem, an efficient energy recovery control strategy is proposed based on the modified nonlinear model predictive control method. Firstly, combined with the characteristics of the compound braking process of single-shaft parallel hybrid electric bus, a 7 degrees of freedom model of the vehicle longitudinal dynamics is built. Secondly, considering nonlinear characteristic of the vehicle model and the efficiency of regenerative braking system, the particle swarm optimization algorithm within the modified nonlinear model predictive control is adopted to optimize the torque distribution between regenerative braking system and pneumatic braking system at the wheels. So as to reduce the computational time of modified nonlinear model predictive control, a nearest point method is employed during the braking process. Finally, the simulation and hardware-in-loop test are carried out on road conditions with different tire–road adhesion coefficients, and the proposed control strategy is verified by comparing it with the conventional control method employed in the baseline vehicle controller. The simulation and hardware-in-loop test results show that the proposed strategy can ensure vehicle safety during emergency braking situation and improve the recovery energy almost 17% compared with the conventional rule-based strategy in the general braking situation. Therefore, the proposed control strategy might offer a theoretical reference for the design of the actual braking controller in engineering practice.

Analysis of Driving Safety Criteria Based on National Regulations for the Suspension Systems of NGVs

The work analyses the technical evaluation process of the suspension system for vehicles that have been adapted to natural-gas-fuelled engines from power light-duty gasoline, and diesel vehicles; this evaluation is done through a mechanical review established by national regulations. The development of this analysis is focused on establishing the relationship between the natural-gas-fuelled equipment and the dynamic effect caused by the extra-weight, according to two measuring criteria that determine the safety and driving comfort, these are: (i) tire-road adhesion index; and (ii) tire excitation phase angle. The paper also proposes new elements that can be added to the current national regulations and that are currently applied to assess the suspension of natural gas vehicles, recorded using a test standard benchmark for the evaluation of the suspension.

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.

Identification of Tire-road Adhesion State on Complicated Road Surface for Traction Control System

In split-μ road,it is easy to create active braking force on the high-μ side wheel in traction control system(TCS),which is due to the error of road adhesion state identification.It makes braking force and driving force consume each other and causes the vehicle shaking.Hence the accuracy and rapidity of tire-road adhesion state identification on complicated road is a key norm to evaluate the robustness of TCS,and a necessary factor to enhance the control effect of TCS.A comprehensive method for identification of road adhesion state is presented in this paper.A fuzzy logic,which adopts the absolute different value of road utilization adhesion coefficient and slip speed between the both sides of driving wheel as inputs,is used in this method.The confidence coefficient is introduced.Road adhesion state is estimated according to the interval in which the value of confidence coefficient locates.The simulation and test verify that the method for identification of road adhesion state is effective and timely.

Study on Electro-Pneumatic Clutch for Automatic Mechanical Transmission

The clutch control is one of the cores and most difficult issues in the development of an AMT system. In this paper the pneumatic clutch engagement characteristic is analyzed. Thereto, a simulation model of an automotive powertrain comprises a diesel engine, drivetrain and wheels driving a vehicle through tire-road adhesion are built using Matlab/Simulink. In the simulation, a refined control law of constant engine speed in part process is proposed and tested. The engaging speed and displacement of the clutch vary with the accelerate paddle opening, engine speed, clutch driven plate speed and gears according the control law. Field experiment results show that the control strategy fulfills the system requirements.

Key Factors Effect on Vehicle Braking Performance Based on Nonlinear 3DOF Vehicle Dynamic Model

3DOF nonlinear braking dynamic model considering tire-road adhesion characteristics was established, and non-dimensional equations were gained from the above mathematic models by using braking torque coefficient, front and rear axle equivalent inertia coefficients and braking force distribution coefficient. Based on the numerical calculation in Matlab-Simulink software, the effect of key factors, (including vehicle mass and vehicle gravity center position variation, frontal and rear braking force distribution coefficient, and frontal and rear axle inertial variation caused by driven mode) on vehicle braking performance, such as braking distance and wheel lockup status, was investigated and summarized. Several 3D visualizations of the simulation results show that variation of vehicle center of gravity, vehicle mass, braking moment distribution, wheel equivalent inertia due to driveline, can cause quite complex effect. It can be assumed that the gained results in this study can help to improve vehicle braking performance and enhance braking stability.

Wheel Slip Control via Second-Order Sliding-Mode Generation

During skid braking and spin acceleration, the driving force exerted by the tires is reduced considerably, and the vehicle cannot speed up or brake as desired. It may become very difficult to control the vehicle under these conditions. To solve this problem, a second-order sliding-mode traction controller is presented in this paper. The controller design is coupled with the design of a suitable sliding-mode observer to estimate the tire-road adhesion coefficient. The traction control is achieved by maintaining the wheel slip at a desired value. In particular, by controlling the wheel slip at the optimal value, the proposed traction control enables antiskid braking and antispin acceleration, thus improving safety in difficult weather conditions, as well as stability during high-performance driving. The choice of second-order sliding-mode control methodology is motivated by its robustness feature with respect to parameter uncertainties and disturbances, which are typical of the automotive context. Moreover, the proposed second-order sliding-mode controller, in contrast to conventional sliding-mode controllers, generates continuous control actions, thus being particularly suitable for application to automotive systems.

Fuzzy Logic Traction Controllers and their Effect on Longitudinal Vehicle Platoon Systems

SUMMARY This paper presents two fuzzy logic traction controllers and investigates their effect on longitudinal platoon systems. A fuzzy logic approach is appealing for traction control because of the nonlinearity and time-varying uncertainty involved in traction control systems The fuzzy logic traction controllers we present regulate brake torque to control wheel slip, which is the normalized difference between wheel and vehicle speed. One fuzzy controller estimates the peak slip corresponding to the maximum tire-road adhesion coefficient and regulates wheel slip at the peak slip. The controller is attractive because of its ability to maximize acceleration and deceleration regardless of road condition. However, we find through simulations the controller's performance degrades in the presence of time-varying uncertainties. The other fuzzy logic controller regulates wheel slip at any desired value. Through simulations we find the controller robust against changing road conditions and uncertainties. The target slip is predetermined and not necessarily the peak slip for all road conditions. If the target slip is set low, stable acceleration and deceleration is guaranteed, regardless of road condition We also study the effect of traction control on longitudinal vehicle platoon systems using simulations. The simulations include acceleration and deceleration maneuvers on an icy road. The results indicate traction control may substantially improve longitudinal platoon performance, especially when icy road conditions exist.