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.     

A modified integral sliding mode control to lateral stabilisation of 4-wheel independent drive electric vehicles

This paper presents a novel sliding mode controller (SMC) and its application in the lateral stability control of a 4-wheel independent drive electric vehicle. The structure of the SMC is modified and online-tuned to ensure vehicle system stability, and to track the desired vehicle motion references when an in-wheel motor fault happens. The proposed controller is faster, more accurate, more robust, and with smaller chattering than common SMCs chatter. The effectiveness of the introduced approach is investigated through conducted simulations in the CARSIM and MATLAB software environments.     

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.     

An adaptive fuzzy-sliding lateral control strategy of automated vehicles based on vision navigation

Lateral control is considered to be one of the toughest challenges in the development of automated vehicles due to their features of nonlinearities, parametric uncertainties and external disturbances. In order to overcome these difficulties, an adaptive fuzzy-sliding mode control strategy used for lateral control of vision-based automated vehicles is proposed in this paper. First, a vision algorithm is designed to provide accurate location information of vehicle relative to reference path. Then, an adaptive fuzzy-sliding mode lateral controller is proposed to counteract parametric uncertainties and strong nonlinearities, and the asymptotic stability of the closed-loop lateral control system is proven by the Lyapunov theory. Finally, experimental results indicate that the proposed algorithm can achieve favourable tracking performance, and it has strong robustness.     

An optimal model-based trajectory following architecture synthesising the lateral adaptive preview strategy and longitudinal velocity planning for highly automated vehicle

Automated driving has received a broad of attentions from the academia and industry, since it is effective to greatly reduce the severity of potential traffic accidents and achieve the ultimate automobile safety and comfort. This paper presents an optimal model-based trajectory following architecture for highly automated vehicle in its driving tasks such as automated guidance or lane keeping, which includes a velocity-planning module, a steering controller and a velocity-tracking controller. The velocity-planning module considering the optimal time-consuming and passenger comforts simultaneously could generate a smooth velocity profile. The robust sliding mode control (SMC) steering controller with adaptive preview time strategy could not only track the target path well, but also avoid a big lateral acceleration occurred in its path-tracking progress due to a fuzzy-adaptive preview time mechanism introduced. In addition, an SMC controller with input–output linearisation method for velocity tracking is built and validated. Simulation results show this trajectory following architecture are effective and feasible for high automated driving vehicle, comparing with the Driver-in-the-Loop simulations performed by an experienced driver and novice driver, respectively. The simulation results demonstrate that the present trajectory following architecture could plan a satisfying longitudinal speed profile, track the target path well and safely when dealing with different road geometry structure, it ensures a good time efficiency and driving comfort simultaneously.     

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.     

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.     

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 control strategy for parallel hybrid electric vehicles based on extremum seeking

An energy management control strategy for a parallel hybrid electric vehicle based on the extremum-seeking method for splitting torque between the internal combustion engine and electric motor is proposed in this paper. The control strategy has two levels of operation: the upper and lower levels. The upper level decision-making controller chooses the vehicle operation mode such as the simultaneous use of the internal combustion engine and electric motor, use of only the electric motor, use of only the internal combustion engine, or regenerative braking. In the simultaneous use of the internal combustion engine and electric motor, the optimum energy distribution between these two sources of energy is determined via the extremum-seeking algorithm that searches for maximum drivetrain efficiency. A dynamic programming solution is also obtained and used to form a benchmark for performance evaluation of the proposed method based on extremum seeking. Detailed simulations using a realistic model are presented to illustrate the effectiveness of the methodology.     

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.     

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

混合动力电动汽车控制策略的研究

主要讨论了并联式混合动力电动汽车的控制策略,详细阐述了控制策略的依据以及控制过程,并给出了控制策略的仿真结果。     

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.     

联合仿真技市在车辆动力学稳定几天控制上的应用

首先介绍了目前车辆动力学稳定性控制的研究现状．提出了基于联合仿真平台进行控制仿真研究的新思路；其次详细分析了车辆动力学稳定性控制的原理。应用直接横摆力矩状态反馈控制策略，基于ADAMS／Car和Matlab／simulink的联合仿真技术．采用阶跃转向和单移线仿真工况有效验证了该控制策略的正确性，提高车辆在危险工况下的稳定性和可控性，为实际设计车辆动力学稳定性控制系统提供了理论基础。     

Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.     

五轴混动汽车电子差速控制策略研究

随着新能源汽车的深入研发,电机驱动控制技术的要求也越来越高,文章主要针对多轴增程式混合动力汽车驱动控制策略进行研究,提出电机驱动控制器设计架构以及电子差速控制策略,通过仿真以及实车测试对文章所提出的驱动控制策略进行验证.     

基于ADAMS整车操纵稳定性分析

利用ADAMS软件,建立整车模型。对整车进行操纵稳定性分析,包括稳态回转、角跃阶输入、低速与高速转向回正以及单移线试验。从而实现了虚拟样机技术的应用,仿真分析整车的操纵稳定性,也验证了模型建立的准确性。     

A review on motorcycle and rider modelling for steering control

The paper is a review of the state of knowledge and understanding of steering control in motorcycles and of the existing rider models. Motorcycles are well known to have specific instability characteristics, which can detrimentally affect the rider's control, and as such a suitable review of these characteristics is covered in the first instance. Next, early models which mostly treat riding as a regulatory task are considered. A rider applies control based on sensory information available to him/her, predominantly from visual perception of a target path. The review therefore extends to cover also the knowledge and research findings into aspects of road preview control. Here, some more emphasis is placed on recent applications of optimal control and model predictive control to the riding task and the motorcycle–rider interaction. The review concludes with some open questions which naturally present a scope for further study.     

A novel vehicle dynamics stability control algorithm based on the hierarchical strategy with constrain of nonlinear tyre forces

Direct yaw moment control (DYC), which differentially brakes the wheels to produce a yaw moment for the vehicle stability in a steering process, is an important part of electric stability control system. In this field, most control methods utilise the active brake pressure with a feedback controller to adjust the braked wheel. However, the method might lead to a control delay or overshoot because of the lack of a quantitative project relationship between target values from the upper stability controller to the lower pressure controller. Meanwhile, the stability controller usually ignores the implementing ability of the tyre forces, which might be restrained by the combined-slip dynamics of the tyre. Therefore, a novel control algorithm of DYC based on the hierarchical control strategy is brought forward in this paper. As for the upper controller, a correctional linear quadratic regulator, which not only contains feedback control but also contains feed forward control, is introduced to deduce the object of the stability yaw moment in order to guarantee the yaw rate and side-slip angle stability. As for the medium and lower controller, the quantitative relationship between the vehicle stability object and the target tyre forces of controlled wheels is proposed to achieve smooth control performance based on a combined-slip tyre model. The simulations with the hardware-in-the-loop platform validate that the proposed algorithm can improve the stability of the vehicle effectively.