Research On Eco-Mode Of Hybrid Powertrain Based On Working Cycles And Drivers' Operating Types

The hybrid powertrain technology has been acknowledged as an effective method to improve vehicle fuel economy and decrease emissions while not sacrificing its dynamic performance,due to the involvement of electric motors and energy storage system.However,when driving in the real world,the level of fuel consumption that the hybrid system is able to save is related to the level of future road and cycle information that can be acquired.How to help the hybrid system achieve its maximum efficiency with the information that can be acquired by our current technology,is a topic worth studying.The work of this paper is based on a Plug-in Hybrid Electric Bus used in the city of Zhuzhou,Hunan.This paper studied the use of two kinds of information in the energy management system,to improve the hybrid system efficiency and decrease its fuel consumption.After studying the working cycle factor and drivers' operating type factor,the author combined the two factors and proposed an Eco-Mode for the hybrid system.Firstly,this paper collected the running data of three No.61 City Bus for one month.By analyzing these data,the author found out that the working cycles of No.61 buses are similar.By using the eigenvalue analysis method,the author built a typical cycle for the No.61 bus,and testified the validity of the typical cycle and the original data.Using this cycle as the input condition,the author built the mathematical model for the optimization problem of the hybrid system used on the city bus.After solving this optimization problem using ECMS algorithm,the author analyzed the actuators' running states and summarized a rule-based optimized energy management strategy.Applying this algorithm on the Simulink model of the city bus,the bus reached a fuel consumption decrease of 9.3%.Second,the drivers' operating pattern factor and its effect to the energy management system was studied.In order to build a mapping relation between the drivers and their fuel economy performance,a method using vehicle speed and acceleration pedal signals to classify different drivers' operating pattern was proposed.By using this method,different drivers in different driving scenario can be classified into one of five drivers' operation types.Each type has its unique characteristic of acceleration pedal using preference,resulting in a certain fuel consumption level.Based on different drivers' operating type,an energy management strategy with different parameters is proposed to optimize the fuel consumption.Applying this algorithm on the Simulink model,the bus reached an average fuel consumption decrease of 4.5% in five types.Third,the author proposed the Eco-Mode algorithm for the hybrid system.The EcoMode algorithm combined the factor of working cycle and drivers' operating type.By capturing the driver's manipulation of the vehicle and acceleration pedal,the algorithm can adjust to different driver types in real-time.By optimizing the hybrid system power distribution among actuators,the vehicle reached a 17.9% fuel economy improvement in MATLAB/Simulink model.The algorithm also decreased the fuel consumption difference between different drivers.