Research On Predictive Energy Saving Control At A Intersection Of Four-wheel Independent Drive Electric Vehicle Based On Eco-driving

Intelligence,connectivity,and electrification are the future development trends of the automotive industry.As an important component of autonomous driving technology,Eco-driving technology is of great significance to reducing vehicle energy consumption.The combination of Eco-driving technology and V2 X Internet of Vehicles technology can perceive road traffic information in advance,and at the same time combine the current state of the vehicle to control the vehicle Eco-driving achieves energy-saving goals.At present,Eco-driving technology is mainly applied to traditional fuel vehicles.Drivers adopting Eco-driving strategies can reduce sudden acceleration,deceleration,idling,and long idling behaviors.In addition,the combination of Eco-driving technology and vehicle-road collaboration technology in urban traffic conditions by obtain information such as signal lamp phase duration,road slope,traffic flow,etc.,based on which drive control strategies can be established to effectively reduce vehicle fuel consumption.Four-wheel hub motors independently drive electric vehicles with independent controllable torque,rapid response,and many characteristics such as braking energy recovery.It is an ideal object for exploring the dynamics of smart vehicles.In order to study the Eco-driving strategy of electric vehicles independently driven by four-wheel hub motors at a intersection,this thesis is based on the Science and Technology Project of Jilin Province Education Department "Distributed electric vehicle dynamic and collaborative control based on chassis-by-wire system"(Project Number: JJKH20200963KJ),establishes a vehicle dynamics model and an vehicle Eco-driving model at a intersection,and selects an instantaneous energy consumption model based on speed and acceleration.The energy consumption model takes the lowest energy consumption as the objective function,uses genetic algorithms to find the target vehicle speed trajectory under current working conditions,and compares the changes with ordinary driving speed trajectories,and analyzes the impact of Eco-driving technology on the energy saving of electric vehicles through testing and verification.Firstly,establish a four-wheel hub motors independently drive electric vehicle model,and design a vehicle speed trajectory tracking control method.Establish vehicle longitudinal dynamics model and tire model based on MATLAB/Simulink,and establish hub motor model considering energy loss;calculate the battery state of charge by the ampere-hour integration method and establish the equivalent circuit model,construct the converter module to calculate the battery charge and discharge current,and get the vehicle brakes to recover energy.Based on the fuzzy PID control method,the vehicle speed trajectory tracking control strategy is designed,and the required driving power is obtained by considering whether the vehicle stops.The accuracy of the vehicle model was verified by the new standard European Cyclic Test(NEDC)and the Japanese Light Vehicle Test(JC08).The verification results show that the proposed fuzzy PID acceleration control strategy can better track the desired vehicle speed trajectory.Secondly,propose the Eco-driving strategy of electric vehicles at the intersection of urban roads and signal lights based on the environment of the Internet of Vehicles.Calculate the time range for the target vehicle to pass through the intersection without stopping according to the current signal light status information at the intersection,analyze the feasibility of the target vehicle’s uniform speed control based on the initial speed and the remaining time before the signal light turns red,and control the speed limit of the road and control the starting line to the intersection distance,calculate the trajectory range of the target vehicle under different scenarios.The instantaneous energy consumption model based on speed and acceleration is selected to establish the lowest energy consumption objective function,and the genetic algorithm is used to find the Eco-driving trajectory of electric vehicles under different working conditions,so as to complete the construction of the vehicle Eco-driving model at signal intersections.Finally,complete the verification of the Eco-driving model of electric vehicles at signal intersections.Carry out real vehicle driving tests at a signal intersection,design test procedures and schemes based on different signal light phase information,let the same driver drive the vehicle in different scenarios,collect vehicle passing signal intersection data information,and use MATLAB to draw vehicle speed-time curves.Calculate the target vehicle speed trajectory under different working conditions through the Eco-driving model,and take the Eco-driving and ordinary driving speed trajectories as input to obtain the electric vehicle energy consumption curve and the battery state of charge curve,etc.,to analyze the vehicle energy consumption under different driving strategies.The research results show that compared with ordinary driving in different scenarios,the vehicle adopts the Eco-driving strategy to save energy about 10.4%～27.3%.It is verified that the proposed Eco-driving strategy for vehicles at signal intersections can effectively reduce the energy consumption of electric vehicles and increase the driving range of vehicles.