Application Of Optimization Control Method In Extended Range Electric Vehicles

The electrification and intelligence are the future development directions of automobile technology,and the technology level of electric control system directly determines the electrification and intellectualized technology level of automobile.Due to the complex system structure and working condition,and the lack of practical optimization method for electric control system,The efficient use and promotion of electric vehicles are restricted.This paper starts with research and development of sensor,vehicle control,battery management and in-car Internet terminal products,the intelligent optimization control method is applied to the vehicle electric control system,which optimize the information processing and power flow of pure and hybrid electric vehicle.The main innovation points include the following aspects:Combined with electric architecture design of car and bus,key components selection matching,and electric control system working mode is discussed for the transmission system architecture of range extended electric vehicle.And the influence factors of driving range and battery charging and discharging are discussed.For the international advanced electric vehicle drive system,the control strategy of optimization method research.An optimization control method based on trip recognition and fruit fly optimization algorithm is proposed to optimize program of electric vehicle charging and discharging strategy,optimal power flow and improve efficiency.For the latest battery management system series standards,the development idea of battery management system is analyzed.The development and optimization of the battery management system is being used as an instance,online identification and operation interval optimization method is proposed to improve battery life.The problems existing in the design of battery management system are analyzed some suggestions for optimizing the design of battery management system are presented.Aiming at the problem of difficult guarantee for electric vehicle driving experience,a dynamic optimization control method based on vehicle state perception and driving intention identification is proposed.A accelerator pedal based on three-axis hall principle is designed,and the driving intention is identified while using particle swarm method to improve the accuracy.The 6 axis inertial navigation system is adopted to accurate perception of vehicle,and combining with driver input information to identify the driving intention.Through adjust the power demand of motor,the dynamic performance of the electric vehicle is optimized.The real vehicle test verifies that this method can effectively reduce the energy consumption of the unit miles while improving the stability of driving.For the safety and innovative networking application of electric vehicles,a remote monitoring system for electric vehicles based on cloud computing technology is developed.In view of the demand of multi-user level,the Hadoop data processing component is adopted to build a large data processing platform for electric vehicles with scalability and expansibility.Finally,the extreme learning machine method is presented to optimize the working conditions of range extended electric vehicle based on large data from cloud monitoring system.Through the use of series method,combined with the research and development of the corresponding electronic control system products,the optimization design of electric vehicle from principle to design to control method is carried out.The use of series method can effectively improve the performance of electric vehicle’s electric control system,reduce energy consumption and improve driving experience.Through the analysis of data,the optimization parameters of electric vehicle structure design are provided,the development efficiency is reduced and the risk is reduced.