Wheel slip control for ground vehicles with individually controlled electric motors can be realized with strategies that can significantly differ from the conventional antilock braking system (ABS) and traction control (TC) system. This paper provides a review of state-of-the-art technology and recent developments in TC and ABSs using the actuation of electric motors. Particular attention is paid to the realization of slip estimators, the formalization of torque demand, and the control methods applied for the implementation of TC and ABSs. The performed analysis allowed for the differentiation of several most elaborated methods for slip and torque control and defining still imperfectly investigated problems to be covered by the further development of TC and ABSs for full electric vehicles.

A Survey of Traction Control and Antilock Braking Systems of Full Electric Vehicles With Individually Controlled Electric Motors

Vibration mitigation for in-wheel switched reluctance motor driven electric vehicle with dynamic vibration absorbing structures

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control Firstly, the vehicle dynamics model (ie, transfer function) is established according to the vehicle parameters Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

To improve vehicle path-following performance and to reduce driver workload, a human-centered feed-forward control (HCFC) system for a vehicle steering system is proposed. To be specific, a novel dynamic control strategy for the steering ratio of vehicle steering systems that treats vehicle speed, lateral deviation, yaw error, and steering angle as the inputs and a driver's expected steering ratio as the output is developed. To determine the parameters of the proposed dynamic control strategy, drivers are classified into three types according to the level of sensitivity to errors, i.e., low, middle, and high. The proposed HCFC system offers a human-centered steering system (HCSS) with a tunable steering gain, which can assist drivers in tracking a given path with smaller steering wheel angles and change rate of the angle by adaptively adjusting steering ratio according to driver's path-following characteristics, reducing the driver's workload. A series of experiments of tracking the centerline of double lane change (DLC) are conducted in CarSim and three different types of drivers are subsequently selected to test in a portable driving simulator under a fixed-speed condition. The simulation and experiment results show that the proposed HCSS with the dynamic control strategy, as compared with the classical control strategy of steering ratio, can improve task performance by about 7% and reduce the driver's physical workload and mental workload by about 35% and 50%, respectively, when following the given path.

Human-Centered Feed-Forward Control of a Vehicle Steering System Based on a Driver's Path-Following Characteristics

This paper presents a lateral motion control strategy for four-wheel independently actuated (FWIA) electric ground vehicles that use the controller area network as a communication medium. The proposed controller design aims to guarantee vehicle stability while tracking the desired yaw rate, in spite of random network-induced delays that exist in both the feedback and forward channels. By modeling the random network-induced delays in both channels as two homogenous Markov chains, statistic information of these delays is incorporated in the mode-dependent tracking controller design. The control law consists of state feedback control and integral control. To fully compensate for the network-induced delays, a delay-free stochastic closed-loop system is first obtained in a discrete-time framework by using a system augmentation technique. Then, a robust linear quadratic regulator-based $\boldsymbol{H}_{\infty}$ controller is developed to achieve the tradeoff between the tracking error and the control input while also attenuating the effect of external disturbance. Considering the physical limitation of in-wheel motors, the eigenvalue positions of the state matrix are constrained in a predefined area to further balance the control inputs and transient responses by using pole placement. Finally, an iterative linear matrix inequality algorithm is adopted to obtain the delay-dependent feedback control gains. Simulation results based on a high-fidelity, CarSim, full-vehicle model show the effectiveness of the proposed lateral motion control approach.

Robust Lateral Motion Control of Electric Ground Vehicles With Random Network-Induced Delays

Electric power steering (EPS) is more and more in use for passenger cars. Compared with hydraulic steering systems there are many advantages, such as reduced CO2 emissions and the possibility to use the EPS motor torque for advanced driver assistance systems. One task of the steering system is to give the driver an adequate steering feel. This includes providing road feedback and the right level of assistance torque. This article describes the steering torque control of a rack-assisted EPS. The controller's task is to follow a reference steering torque quickly and accurately. First, a mechanical model of the EPS is shown. Then, an H∞-controller is designed, implemented and compared with other steering torque controllers. As steering torque discontinuities are a topic when looking at new control algorithms, the phenomenon and its cause are analysed using a detailed mechanical model. The results of this analysis are considered in the controller design.

H∞-control of a rack-assisted electric power steering system

This article presents a motion controller for a road vehicle equipped with a steer-by-wire system and four independent electric rim-mounted drives. The motion controller separates the control law from the specific actuator setup by the usage of virtual global control variables acting on the vehicle centre of gravity. A control allocation algorithm distributes the virtual control variables to the available actuators. An approximation of the real actuator dynamics is used to analyse the performance of different motion controller types in the linear and nonlinear driving regions. In addition, a vehicle state observer consisting of a traction force observer and an unscented Kalman filter is discussed to analyse the control behaviour in the case of a real sensor setup.

Control performance of a road vehicle with four independent single-wheel electric motors and steer-by-wire system

Many present-day’s vehicles are equipped with adaptive cruise control systems (ACC). The purpose of these systems is to keep a desired vehicle speed or distance towards a preceding object vehicle, if existing. Yet, present ACC systems do not consider the vehicle’s fuel consumption in a satisfactory way. For example, while platooning, a lot of fuel is wasted by vehicle drivers who imitate their respective preceding vehicles’ speed profiles. In contrast, copying these speed variations is not necessary, as it does not decrease the overall travel time but increases the fuel rate. Instead, allowing a dynamic distance towards an object vehicle decreases the subject vehicle’s fuel consumption because the engine can be run in fuel efficient operating points for a longer length of time.

Steffen Müller

Papers

H∞-control of a rack-assisted electric power steering system

Control performance of a road vehicle with four independent single-wheel electric motors and steer-by-wire system

A Model Predictive Approach for a Fuel Efficient Cruise Control System

Effizienzpotenziale durch Elektrifizierung bei mobilen Arbeitsmaschinen

Modellbasierte Regler- und Funktionsentwicklung Für mechatronische Lenksysteme