A novel integrated chassis controller for full drive-by-wire vehicles

In this paper, a systematic design with multiple hierarchical layers is adopted in the integrated chassis controller for full drive-by-wire vehicles. A reference model and the optimal preview acceleration driver model are utilised in the driver control layer to describe and realise the driver's anticipation of the vehicle's handling characteristics, respectively. Both the sliding mode control and terminal sliding mode control techniques are employed in the vehicle motion control (MC) layer to determine the MC efforts such that better tracking performance can be attained. In the tyre force allocation layer, a polygonal simplification method is proposed to deal with the constraints of the tyre adhesive limits efficiently and effectively, whereby the load transfer due to both roll and pitch is also taken into account which directly affects the constraints. By calculating the motor torque and steering angle of each wheel in the executive layer, the total workload of four wheels is minimised during normal driving, whereas the MC efforts are maximised in extreme handling conditions. The proposed controller is validated through simulation to improve vehicle stability and handling performance in both open- and closed-loop manoeuvres.     

Stability control of 4WS vehicles using robust IMC techniques

A robust nonparametric approach to vehicle stability control by means of a four-wheel steer by wire system is introduced. Both yaw rate and sideslip angle feedbacks are used in order to effectively take into account safety as well as handling performances. Reference courses for yaw rate and sideslip angle are computed on the basis of the vehicle speed and the handwheel angle imposed by the driver. An output multiplicative model set is used to describe the uncertainty arising from a wide range of vehicle operating situations. The effects of saturation of the control variables (i.e. front and rear steering angles) are taken into account by adopting enhanced internal model control methodologies in the design of the feedback controller. Actuator dynamics are considered in the controller design. Improvements on understeer characteristics, stability in demanding conditions such as turning on low friction surfaces, damping properties in impulsive manoeuvres, and improved handling in closed loop (i.e. with driver feedback) manoeuvres are shown through extensive simulation results performed on an accurate 14 degrees of freedom nonlinear model, which proved to give good modelling results as compared with collected experimental data.     

Sliding-mode control for the roll-angle tracking of an unmanned bicycle

This study investigates the roll-angle tracking control of an unmanned bicycle using a sliding-mode controller (SMC). The roll angle is controlled at a specific speed via a simple proportional, derivative (PD) controller to generate input–output data including steering torque as well as roll and steering angles. The collected data are then used to identify a one-input two-output linear model by a prediction-error identification method using parameterisation in a canonical state-space form derived as a Whipple model. Once the linear model is obtained, the SMC can be designed to control the bicycle. Simulations and comparisons with a proportional, integral, derivative (PID) controller show that this SMC is robust against changes and variations in speed as well as external disturbances.     

A driver-adaptive stability control strategy for sport utility vehicles

Conventional vehicle stability control (VSC) systems are designed for average drivers. For a driver with a good driving skill, the VSC systems may be redundant; for a driver with a poor driving skill, the VSC intervention may be inadequate. To increase safety of sport utility vehicles (SUVs), this paper proposes a novel driver-adaptive VSC (DAVSC) strategy based on scaling the target yaw rate commanded by the driver. The DAVSC system is adaptive to drivers’ driving skills. More control effort would be exerted for drivers with poor driving skills, and vice versa. A sliding mode control (SMC)-based differential braking (DB) controller is designed using a three degrees of freedom (DOF) yaw-plane model. An eight DOF nonlinear yaw-roll model is used to simulate the SUV dynamics. Two driver models, namely longitudinal and lateral, are used to ‘drive’ the virtual SUV. By integrating the virtual SUV, the DB controller, and the driver models, the performance of the DAVSC system is investigated. The simulations demonstrate the effectiveness of the DAVSC strategy.     

Vehicle dynamic stability improvements through gain-scheduled steering and braking control

This paper is concerned with the synthesis of a robust gain-scheduled ?_∞ MIMO vehicle dynamic stability controller (VDSC) involving both steering and rear braking actuators. This VDSC aims at improving automotive vehicle yaw stability and lateral performances. The aim of this work is to provide a methodology to synthesise such a controller while taking into account the braking actuator limitations and use the steering actuator only if it is necessary. These objectives are treated in an original way by the synthesis of a parameter-dependent controller built in the LPV framework and by the solution of an LMI problem. The proposed solution is coupled with a local ABS strategy to guarantee slip stability and make the solution complete. Nonlinear time and frequency domain simulations on a complex full vehicle model (which has been validated on a real car), subject to critical driving situations, show the efficiency and robustness of the proposed solution.     

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework.     

A fundamental investigation of tilt control systems for narrow commuter vehicles

One way of addressing traffic congestion is by efficiently utilizing the existing highway infrastructure. Narrow tilting vehicles that need a reduced width lane can be part of the solution if they can be designed to be safe, stable, and easy to operate. In this paper, a control system that stabilizes the tilt mode of such a vehicle without affecting the handling of the vehicle is proposed. This control system is a combination of two different types of control schemes known as steering tilt control (STC) and direct tilt control (DTC) systems. First, different existing variations of both STC and DTC systems are considered and their shortcomings analysed. Modified control schemes are then suggested to overcome the deficiencies. Then a new method of integrating these two control schemes that guarantees smooth switchover between the controllers as a function of vehicle velocity is proposed. The performance of the proposed STC, DTC, and integrated systems is evaluated by carrying out simulations for different operating conditions and some experimental work. The design of a second-generation narrow tilting vehicle on which the developed control system has been implemented is presented.     

A fundamental investigation of tilt control systems for narrow commuter vehicles

One way of addressing traffic congestion is by efficiently utilizing the existing highway infrastructure. Narrow tilting vehicles that need a reduced width lane can be part of the solution if they can be designed to be safe, stable, and easy to operate. In this paper, a control system that stabilizes the tilt mode of such a vehicle without affecting the handling of the vehicle is proposed. This control system is a combination of two different types of control schemes known as steering tilt control (STC) and direct tilt control (DTC) systems. First, different existing variations of both STC and DTC systems are considered and their shortcomings analysed. Modified control schemes are then suggested to overcome the deficiencies. Then a new method of integrating these two control schemes that guarantees smooth switchover between the controllers as a function of vehicle velocity is proposed. The performance of the proposed STC, DTC, and integrated systems is evaluated by carrying out simulations for different operating conditions and some experimental work. The design of a second-generation narrow tilting vehicle on which the developed control system has been implemented is presented.     

Vehicle stability control using direct virtual sensors

The paper investigates the use of a direct virtual sensor (DVS) to replace a physical sensor in a vehicle stability control system. A yaw control system is considered and the proposed solution can be particularly useful when a fault of the yaw rate physical sensor occurs. A DVS is a stable linear filter derived directly from input–output data, collected in a preliminary experiment. In this work, it is shown that, by using data collected in a closed-loop fashion, better DVS accuracy can be obtained with a reduced number of measured variables. Moreover, the robust stability of the closed-loop system employing a DVS is studied. The effectiveness of the presented results is shown through numerical simulations of harsh manoeuvres, performed using a detailed model of a vehicle equipped with an active front steering device.     

Independent control of all-wheel-drive torque distribution

The sophistication of all-wheel-drive (AWD) technology is approaching the point where the drive torque to each wheel can be independently controlled. This potentially offers vehicle handling enhancements similar to those provided by dynamic stability control, but without the inevitable reduction in vehicle acceleration. Independent control of AWD torque distribution would therefore be especially beneficial under acceleration close to the limit of stability. A vehicle model of a typical sports sedan was developed in Simulink, with fully independent control of torque distribution. Box-Behnken experimental design was employed to determine which torque distribution parameters have the greatest impact on the vehicle course and acceleration. A proportional-integral control strategy was implemented, applying yaw rate feedback to vary the front-rear torque distribution and lateral acceleration feedback to adjust the left-right distribution. The resulting system shows a significant improvement over conventional driveline configurations under aggressive cornering acceleration on a high-μ surface. The performance approaches the theoretical limit for these conditions. In the medium term, such a system is only likely to be economically viable for premium vehicles. However, a future revolution of powertrain technology towards, for example, wheel-mounted motors, could realize these handling benefits far more widely.     

Robust gain-scheduling automatic steering control of unmanned ground vehicles under velocity-varying motion

Owing to the fact that unmanned ground vehicles have the features of time-varying, parametric uncertainties and external disturbances, this paper mainly studies robust automatic steering control of unmanned ground vehicles. Firstly, a linear parameter varying lateral model for unmanned ground vehicle is constructed, in which the longitudinal velocity is represented by a polytope with finite vertices. Secondly, a robust gain scheduling automatic steering control scheme based on the linear matrix inequality technique is proposed to deal with the characteristics of time-varying and external disturbances. Finally, Simulation results based on Adams–Matlab joint platform using a nonlinear full vehicle model have demonstrated that the proposed control approach can simultaneously ensure the control accuracy and strong robustness of system.     

Real-time model predictive control of connected electric vehicles

ABSTRACT

Electric Vehicles (EVs) motors develop high torque at low speeds, resulting in a high rate of acceleration with the added advantage of being fitted with smaller gearboxes. However, a rapid rise of torque in EVs fitted with central drive powertrains can create undesired torsional oscillations, which are influenced by wheel slip and flexibility in the halfshaft. These torsional oscillations in the halfshaft lead to longitudinal oscillations in the vehicle, thus creating problems with regard to comfort and drivability. The significance of using wheel slip in addition to halfshaft torsion for design of anti-jerk controllers for EVs has already been highlighted in our previous research. In this research, we have designed a look-ahead model predictive controller (LA-MPC) that calculates the required motor torque demand to meet the dual objectives of increased traction and anti-jerk control. The designed LA-MPC will improve drivability and energy consumption in connected EVs. The real-time capability of the LA-MPC has been demonstrated through hardware-in-the-loop experiments. The performance of the LA-MPC has been compared to other controllers presented in the literature. A validated high-fidelity longitudinal-dynamics model of the Rav4EV, which is the test vehicle of our research has been used to evaluate the controller.     

A semi-active control suspension system for railway vehicles with magnetorheological fluid dampers

The high-speed train has achieved great progress in the last decades. It is one of the most important modes of transportation between cities. With the rapid development of the high-speed train, its safety issue is paid much more attention than ever before. To improve the stability of the vehicle with high speed, extra dampers (i.e. anti-hunting damper) are used in the traditional bogies with passive suspension system. However, the curving performance of the vehicle is undermined due to the extra lateral force generated by the dampers. The active suspension systems proposed in the last decades attempt to solve the vehicle steering issue. However, the active suspension systems need extra actuators driven by electrical power or hydraulic power. There are some implementation and even safety issues which are not easy to be overcome. In this paper, an innovative semi-active controlled lateral suspension system for railway vehicles is proposed. Four magnetorheological fluid dampers are fixed to the primary suspension system of each bogie. They are controlled by online controllers for enhancing the running stability on the straight track line on the one hand and further improving the curving performance by controlling the damper force on the other hand. Two control strategies are proposed in the light of the pure rolling concept. The effectiveness of the proposed strategies is demonstrated by SIMPACK and Matlab co-simulation for a full railway vehicle with two conventional bogies.     

Considerations on active control of crosswind stability of railway vehicles

The DLR research project Next Generation Train deals with concepts, methods and technologies for a very high-speed train in double-deck configuration and light-weight design. Due to these three key features, crosswind stability is a particular subject of study. It is shown that conventional approaches here fall short of guaranteeing safety in high-wind occurrences according to the given homologation standards. Therefore, this paper discusses the feasibility of different approaches to ensure crosswind stability by means of active control. Four different concepts are overviewed, the most promising one is then chosen und examined in detailed multibody simulations that are based on data from wind tunnel measurements of the Next Generation Train.     

Identification of linear handling models for road vehicles

This study reports the identification of linear handling models for road vehicles starting from structural identifiability analysis, continuing with the experiments to acquire data on a vehicle equipped with a sensor set and data acquisition system, and ending with the estimation of parameters using the collected data. The model structure originates from the well-known linear bicycle model that is frequently used in handling analysis of road vehicles. Physical parameters of the bicycle model structure are selected as the unknown parameter set that is to be identified. Global identifiability of the model structure is analysed, in detail, and concluded according to various available sensor sets. Physical parameters of the bicycle model structure are estimated using prediction error estimation method. Genetic algorithms are used in the optimisation phase of the identification algorithm to overcome the difficulty in the selection of initial values for parameter estimates. Validation analysis of the identified model is also presented. The identified model is shown to track the system response successfully.     

Integrated control of ground vehicles dynamics via advanced terminal sliding mode control

An integrated vehicle dynamics control (IVDC) algorithm, developed for improving vehicle handling and stability under critical lateral motions, is discussed in this paper. The IVDC system utilises integral and nonsingular fast terminal sliding mode (NFTSM) control strategies and coordinates active front steering (AFS) and direct yaw moment control (DYC) systems. When the vehicle is in the normal driving situation, the AFS system provides handling enhancement. If the vehicle reaches its handling limit, both AFS and DYC are then integrated to ensure the vehicle stability. The major contribution of this paper is in improving the transient response of the vehicle yaw rate and sideslip angle tracking controllers by implementing advanced types of sliding mode strategies, namely integral terminal sliding mode and NFTSM, in the IVDC system. Simulation results demonstrate that the developed control algorithm for the IVDC system not only has strong robustness against uncertainties but also improves the transient response of the control system.     

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.     

Design of safety-oriented control allocation strategies for overactuated electric vehicles

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre–road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.     

Hybrid state-feedback sliding-mode controller using fuzzy logic for four-wheel-steering vehicles

This paper presents a fuzzy controller for high-speed four-wheel-steering (4WS) vehicles based on the state-feedback and the sliding-mode control methods. In the proposed fuzzy controller, the consequent part of the fuzzy IF-THEN rules consists of either a sliding-mode controller or a state-feedback controller. Also, it will be proved that, if every fuzzy rule is stable in the sense of Lyapunov for a general Lyapunov function, defined for the whole system, then the whole system is stable in the sense of Lyapunov. The effectiveness of the proposed method for handling improvement of the 4WS systems will be demonstrated by simulations using a nonlinear vehicle model. The simulation results show that the proposed control method can enhance the dynamic response of the 4WS vehicles by reducing the transient response time and improving vehicle stability as compared to the sliding-mode and the fuzzy sliding-mode control methods.