Automated Generation of Energy Efficient Drive Cycles for Electric Vehicles Considering Limiting Factors

Abstract

Electric Vehicles (EV) are considered as future of the automotive industry due to clean and environment-friendly propulsion but are criticized for their limited range compared to conventional fuel-driven vehicles. In this paper, first of all, the development and validation of a longitudinal vehicle dynamics model for a practical EV is described. Based on the model, the EV dynamic performance characteristics like maximum gradient it can handle and maximum achievable acceleration and speed are evaluated through theoretical expressions. Further, the driving pattern dramatically influences the energy consumed in electric vehicles over a path. In this paper, a simple framework is proposed for automatically generating energy-efficient drive cycles for a practical EV, considering several limiting factors together. Since the most energy-efficient drive cycle may not be the fastest one, a user-defined weight factor based on time and energy tradeoff is incorporated in the framework to generate drive cycles based on user requirements. Such automated drive cycles generated, can provide targeted speed profiles to drivers of EVs before their start of the journey, thus saving energy. The performance of the described method is illustrated and analyzed through results.