Motion Control Of Electric Vehicle Research Articles

Longitudinal Modelling and Control of In-Wheel-Motor Electric Vehicles as Multi-Agent Systems

This paper deals with longitudinal motion control of electric vehicles (EVs) driven by in-wheel-motors (IWMs). It shows that the IWM-EV is fundamentally a multi-agent system with physical interaction. Three ways to model the IWM-EV are proposed, and each is applicable to certain control objectives. Firstly, a nonlinear model with hierarchical structure is established, and it can be used for passivity-based motion control. Secondly, a linearized model with rank-1 interconnection matrix is presented for stability analysis. Thirdly, a time-varying state-space model is proposed for optimal control using linear quadratic regulator (LQR). The proposed modellings contribute the new understanding of IWM-EV dynamics from the view point of multi-agent-system theory. By choosing the suitable control theory for each model, the complexity level of system design is maintained constant, no matter what the number of IWMs installed to the vehicle body. The effectiveness of three models and their design approaches are discussed by several examples with Matlab/Carsim co-simulator.

Rendering Optimal Design in Controlling Fuzzy Dynamical Systems: A Cooperative Game Approach

This study investigates the robust control for uncertain dynamical systems. The uncertainty is (possibly fast) time-varying but bounded. We adopt the fuzzy set theory to describe the uncertainty in the system (hence, called the fuzzy dynamical system). A class of robust controls is proposed based on tunable parameters. The controls are deterministic and are not conventional IF–THEN fuzzy rules based (such as Mamdani type). The proposed controls are able to guarantee deterministic system performance, namely uniform boundedness and uniform ultimate boundedness. In the phase of searching for the optima from the pool of admissible control design parameters, we formulate this as a two-player cooperative game by developing two performance indexes (i.e., the cost functions), each of which is dominated by one tunable parameter (i.e., the player). By the cooperative game theory, we are able to obtain the Pareto-optimality (i.e., the optima of tunable parameters). Simulation results on an electric vehicle motion control problem are presented for demonstration.

Advanced Motion Control of Electric Vehicles Based on Robust Lateral Tire Force Control via Active Front Steering

This paper presents a new motion control method based on robust lateral tire force control (LTFC) to improve vehicle stability or maneuverability. During cornering, vehicle motion is totally governed by lateral forces acting on tires. Thus, the real-time information on tire forces provides advantages in vehicle motion control. Since the lateral tire force measurements are available by using multisensing hub (MSHub) units which were invented by NSK Ltd., the direct LTFC is realizable via active front steering. In control design, a robust control method, e.g., two degree-of-freedom control (2-DOF) with a disturbance observer, is used for improving the reference tracking performance. Moreover, the stability of the proposed control system is discussed by using small gain theorem. The proposed motion controller is implemented on an experimental in-wheel-motor-driven electric vehicle and its performance and effectiveness are verified by field tests. Finally, practical applications of lateral tire force sensors to vehicle motion control systems are discussed.

The Implement of CANopen in Motion Control of Electric Vehicle

Considering the bad electromagnetic environment of electric vehicle, a stable communication system is necessary. Because of its unique stability, CAN bus has been widely used in the field of automotive electronics. CANopen is a higher layer protocol of CAN bus, it has the advantages of conciseness and open-source. In this passage, based on sub-protocol DS301 and DS402, the implement of CANopen in motion control is introduced. The establishment of object dictionary and motor application object is the main content in this article.

Basic Design of Electric Vehicle Motion Control System Using Single Antenna GPS Receiver

By integrating a single antenna GPS receiver and dynamic sensors, key states for electric vehicle motion control system can be estimated, including yaw angle, sideslip angle, longitudinal velocity, and lateral velocity. In order to achieve accurate state estimation, Kalman filter with disturbance accommodating technique considering the handling of time delay in measurements using GPS is proposed. In this paper, three motion controls of electric vehicle based on the estimated states are demonstrated. The first is attitude control using front steering angle with feedback-feedforward controller and disturbance observer. The second is a traction control based on wheel slip ratio control system using sliding mode control theory. The last is lateral stability control using estimated sideslip angle.

Electric Vehicle Traction Control: A New MTTE Methodology

In motion control of electric vehicles (EVs), the undetectable road conditions and varying vehicle parameters challenge the steering ability and validity. This article investigates a new traction control (TC) approach that uses the maximum transmissible torque estimation (MTTE) scheme to carry out the antislip control of EVs. A closed-loop disturbance observer is employed to enhance the steering stability and to improve the robustness on perturbation in wheel inertia of the MTTE approach. This proposed scheme, which contains the closed-loop friction torque estimator, does not require the use of any differentiator. Additionally, the inversion of the controlled plant is unnecessary. The real experiment demonstrated the effectiveness and feasibility of the presented antislip strategy.

Motion Control of Electric Vehicle with In-wheel Motor and Tire Lateral Force Sensor

Motion Control of Electric Vehicle with In-wheel Motor and Tire Lateral Force Sensor

A Novel Traction Control without Chassis Velocity for Electric Vehicles

Research on motion control of electric vehicles has progressed considerably, but traction control has not been so sophisticated and practical because the velocity of vehicles and the friction force are immeasurable. This work takes advantage of the features of driving motors to estimate the maximum transmissible torque output in real time based on a purely kinematic relationship, and then proposes an innovative controller to follow the estimated value directly and constrain the torque reference for slip prevention. By comparison with prior control methods, the resulting control design approach is shown to be more effective and robust on an experimental electric vehicle. In addition, a new architecture for a two-dimensional vehicle stability control system is introduced based on the proposed traction control.

A Novel Traction Control for EV Based on Maximum Transmissible Torque Estimation

Controlling an immeasurable state with an indirect control input is a difficult problem faced in traction control of vehicles. Research on motion control of electric vehicles (EVs) has progressed considerably, but traction control has not been so sophisticated and practical because of this difficulty. Therefore, this paper takes advantage of the features of driving motors to estimate the maximum transmissible torque output in real time based on a purely kinematic relationship. An innovative controller that follows the estimated value directly and constrains the torque reference for slip prevention is then proposed. By analysis and comparison with prior control methods, the resulting control design approach is shown to be more effective and more practical, both in simulation and on an experimental EV.

Motion control of electric vehicles and prospects of supercapacitors

AbstractNovel motion control techniques for electric vehicles (EVs) on the basis of the quick torque generation in these vehicles have been developed at the Hori Laboratory. Because EVs are powered by electric motors, they have three major advantages: (i) motor torque generation is quick and accurate, (ii) a motor can be attached to each wheel, and (iii) motor torque can be estimated precisely. These advantages enable us to (i) easily realize high‐performance antilock braking systems and traction control systems with minor feedback control of each wheel, (ii) control chassis motion, for example, direct yaw control, and (iii) estimate road surface condition. We have developed test vehicles and confirmed the effectiveness of the proposed methods. Recently, we have manufactured small EVs that are powered only by supercapacitors. Supercapacitors have long operating life, large current density, and are environmental friendly. Furthermore, their energy level can be estimated from their terminal voltage. Because EVs powered by supercapacitors can run for more than 20 min by charging only for 30 s, recharging EVs will not be a major problem. In the future, EVs will be recharged via contactless power transfer. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Advanced motion control of electric vehicle with fast minor feedback loops: basic experiments using the 4-wheel motored EV “UOT Electric March II”

Electric motors in electric vehicles (EVs) has quite fast torque response, thus fast minor feedback loops can be applied for vehicle motion stabilization. This paper clarified that such feedback loop can stabilize the dynamics of driven wheel on the slippery road surface. With such loop, driven wheel has large inertia equivalently. It can stabilize the vehicle's lateral dynamics, if minor feedback loops are independently installed in the driven wheels. This effect was demonstrated with simulations and experiments. It suggests the effectiveness of minor feedback loops in the total control system like direct yaw moment control (DYC). This paper also introduces our novel 4-motored EV “UOT Electric March II”, which is newly constructed for these experiments.

Electric Vehicle Related Technologies. Motion Control of Electric Vehicles by Distribution Control of Traction Forces.

This paper proposes a new method to improve the handling and stability of electric vehicles by controlling the yaw moment generated by driving/braking forces. Yaw moment is controlled by the feedforward compensation of steering angle (and steering velocity) to minimize the side slip angle at the vehicle center of gravity. To realize this kind of yaw moment control, the right and left driving/braking forces should be controlled independently. Theoretical analysis and computer simulation are carried out to show the effectiveness of this control system. The results show that the handling and stability are improved significantly compared to those of the conventional two-wheel-steering vehicles, and that a 4WS-equivalent vehicle performance is obtained. This control effectiveness is also verified by experimental results using a downsized vehicle model on a moving belt tester.