Decentralized Dynamic Event-Triggered Communication and Active Suspension Control of In-Wheel Motor Driven Electric Vehicles with Dynamic Damping

This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second,a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.

Torque Distribution of Electric Vehicle with Four In-Wheel Motors Based on Road Adhesion Margin

With the worsening of energy crisis and environmental pollution,electric vehicles with four in?wheel motors have been paid more and more attention. The main research subject is how to reasonably distribute the driving torque of each wheel. Considering the longitudinal motion,lateral motion,yaw movement and rotation of the four wheels,the tire model and the seven DOF dynamic model of the vehicle are established in this paper. Then,the torque distribution method is proposed based on road adhesion margin,which can be divided into anti ? slip control layer and torque distribution layer. The anti?slip control layer is built based on sliding mode variable structure control,whose main function is to avoid the excessive slip of wheels caused by road conditions. The torque distribution layer is responsible for selecting the torque distribution method based on road adhesion margin. The simulation results show that the proposed torque distribution method can ensure the vehicle quickly adapt to current road adhesion conditions,and improve the handling stability and dynamic performance of the vehicle in the driving process.

Multi-objective Optimization of Differential Steering System of Electric Vehicle with Motorized Wheels

A differential steering system is presented for electric vehicle with motorized wheels and a dynamic model of three-freedom car is built.Based on these models,the quantitative expressions of the road feel,sensitivity,and operation stability of the steering are derived.Then,according to the features of multi-constrained optimization of multi-objective function,a multi-island genetic algorithm(MIGA)is designed.Taking the road feel and the sensitivity of the steering as optimization objectives and the operation stability of the steering as a constraint,the system parameters are optimized.The simulation results show that the system optimized with MIGA can improve the steering road feel,and guarantee the operation stability and steering sensibility.

The use of permanent magnet motor for Tesla electric vehicle stimulates the demand for rare earth Nd

On March 13th,Reuters reported that the long run version of Tesla Model 3 will use permanent magnet motors.One of the materials for this type of motor is rare earth metal neodymium,which will further increase the supply pressure of neodymium.Governments around the world are committed to reducing the harmful emissions produced by fossil fuel cars,pushing up demand for electric vehicles

Primary studies on integration optimization of differential steering of electric vehicle with motorized wheels based on quality engineering

The model of the differential steering system(DSS) of electric vehicle with motorized wheels and the three-degree-of-freedom dynamic model of vehicle are built.Based on these models,the concepts and quantitative expressions of steering road feel,steering portability and steering stability are proposed.Through integrating the Monte Carlo descriptive sampling,elitist non-dominated sorting genetic algorithm(NSGA-II) and Taguchi robust design method,the system parameters are optimized with steering road feel and steering portability as optimization targets,and steering stability and steering portability as constraints.The simulation results show that the system optimized based on quality engineering can improve the steering road feel,guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the electric vehicle with motorized wheels system.

Multidiscipline collaborative optimization of differential steering system of electric vehicle with motorized wheels

Based on the multidiscipline design optimization theory, a multidiscipline collaborative optimization model of the differential steering system of electric vehicle with motorized wheels is built, with the steering economy as the main system and the steering road feel, the steering flexibility and the mechanic character of the steering sensors as the subsystems. Considering the coupled relationship of each discipline, the main system is optimized by the multi-island algorithm and the subsystems are optimized by the sequential quadratic programming algorithm. The simulation results show that the steering economy can be optimized by the collaborative optimization, and that the system can get good steering road feel, good steering flexibility and good mechanic character of the steering sensors.

Modeling and Testing of the Multi-pole Field of a Motor for Pure Electric Vehicles

From the principles of electromechanical energy conversion and electromagnetic torque generation, our study evaluatedthe mathematical model of the electromagnetic torque and the vector control method of motors. An analysis of motor typesindicates that the electromechanical energy conversion component is interchangeable. Three distinct types of motor structures,namely DC, induction, and synchronous, are possible, all three being commonly used in pure electric vehicles. For each motortype, simulation models were developed using Modelica, a modeling language for object-oriented multi-domain physicalsystem. A test model of each motor type was configured in the MWorks simulation platform. With a representative motor,specifically the permanent-magnet DC motor, the asynchronous induction motor, and the permanent-magnet synchronousmotor, mechanical properties were simulated and analyzed. The simulation results show that the characteristics of each motormodel are consistent with the theoretical and engineering performance of the representative motor. Therefore, modeling,motor control, and performance testing of a unified multi-pole-field motor, which is used in pure electric vehicles, have beenachieved.