Dynamic Programming Based Research Of Regenerative Braking Energy Recovery For The Hybrid Electric Bus While Pulling In

The energy crisis is becoming increasingly serious.Therefore,new-energy automobile represented by hybrid vehicles are being widely accepted.At the same time,as a key technology for energy saving and emission reduction of hybrid vehicles,the braking energy recovery technology can effectively increase the vehicle’s cruising range and improve the energy efficiency.However,how to maximize the braking energy recovery efficiency under the premise of ensuring the safety performance is still an urgent problem to be solved.In this study,a hybrid electric bus(HEB)equipped with an automatic mechanical transmission(AMT)is used as a research object.And a regenerative braking strategy combined with downshifting is proposed.First,a hybrid bus is taken as the research object,and a three-degree-of-freedom vehicle longitudinal model is established.The characteristics of the single-shift parallel configuration are analyzed,and a simulation model of key components of the vehicle is established based on MATLAB / Simulink.Then,the efficiency improvement of braking energy conservation when downshifting during braking is analyzed.A real-time downshifting strategy based on rule-based and a global downshifting strategy based on the dynamic programming algorithm is designed to analyze the impact of the downshifting process for braking energy recycling.For hybrid vehicles equipped with an automatic manual transmission,downshifting during braking can effectively improve the efficiency of braking energy conservation.However,there is a power interruption during shifting that can cause some loss of regenerative energy.Therefore,the choice of the downshifting point during braking has an important impact on energy recovery efficiency.This study uses the data of 303 bus conditions collected in Chongqing to extract the characteristics of braking conditions,analyzes the general characteristics of the braking process of urban buses,and proposes a dynamic programming-rule based strategy(DPRB).This strategy is divided into two stages: offline data processing and online decision-making.Corresponding to the speed threshold,look-up tables are formed offline using multiple sets of historical data and a dynamic programming algorithm.The dimensions of time and space named the Medium-Time-Distance(MTD)are proposed in order to define the boundary conditions of the running vehicle.Then based on the real-time driving data,the determination of whether to enter the optimal gear selection process in the moment was decided online.Lastly,simulations and hardware-in-loop(HIL)tests were carried out,and the results showed that with the proposed strategy,the fuel consumption per 100 kilometers is reduced effectively in a single urban bus driving cycle.