Connected Electric Vehicle Routing Plan And Energy-efficient Control

Nowadays,the electric vehicle(EV),battergy and motors are the major research topic of automobile industry all over the world.However,due to the disadvantages of the low energy density of electric battery and overly long charging time,the usability of EVs is still uncomparable to traditional vehicles.In recent years,with the rapid development of intelligent transportation systems,the real time short range communication informations like vehicle to vehicle and vehicle to infrastructre communication,as well as the long range communication informations like traffic information and weather information,are now available to EVs and better awareness of the movement of surrounding vehicles and traffic situation ahead are now achievable and better driving performance of EV can be expected.In this paper,considering two typical wireless communication technology based research scenarios,the connected EV travel route planning and EV energy-efficient driving control are studied.In order to optimize the multi objectives of travel plan of EV and fulfil the driver's travel needs,the strong interaction relationship among the travel objectives,travel constraints and travel strategies are considered,and the multi-objective and multi-constraints EV travel plan optimization problems are established.Considering the stochastic time-dependent traffic network environment,the time-aware multi-objective ant colony optimization method is introduced to search the optimal travel plans.With recursive optimization procedure,the travel plan including the travel routes,travel velocity,charging strategy and air-conditioning usage are optimized,and optimal travel plans can be presented to the EV.In order to reduce the driving energy consumption of EV,preceding vehicle movement prediction information is obtained based on wireless communication information,and the nonlinear model predictive control method is established based on the economy,safety and comfort requirements,to build the energy-efficient controller for the distributed EV,therefore the EV driving energy can be reduced based on the movement prediction of preceding vehicle.Aiming to optimize the total energy consumption of EV platoon,the hybrid system theory is applied to identify the key parameters of EVs,and hybrid model predictive control theory is applied to build the energy-efficient control algorithm for the EV platoons to reduce the energy consumption and improve platoon safety.The energy saving performance is studied under different front vehicle input,communication configuration,communication informations,and road slope.In order to prove the effectiveness of the EV energy-efficient control method,explicit model predictive controller is built on the dynamic driving simulator,and hardware-in-loop experiment is conducted.From the experiment results,compared with the traditional driving control method without the preceding vehicle movement prediction,the energy saving performance can be observed based on the proposed energy-efficient controller.