Integrated multistep Markov-based velocity predictor of energy consumption prediction model for battery electric vehicles

Battery electric vehicle (BEV) has been thought as a key factor in decreasing global greenhouse gas emissions and energy conservation. Therefore, recent developments in BEVs have heightened the need for energy consumption prediction. In this paper, an effectively model in virtue of the accurate velocity prediction approach is proposed. Prior to commencing the study, road information and historical driving data are sought from electronic map and realistic road tests respectively. Following processing for these raw data, a semi-physical and semi-empirical model is introduced to tackle the problem for energy consumption calculation. For the velocity prediction, a Markov-chain-based method in conjunction with road information is proposed, which endows energy consumption model with precise velocity profile as input to obtain final results. The feasibility and precision of this method were validated on various road types with acceptable results exhibiting a mean error of less than 2%, highlighting its anticipated preferable performance.