Energy Consumption Modeling And Cruising Range Estimation Based On Driving Cycle For Electric Vehicles

Recently, with the rapid growth of gasoline and diesel powered vehicles, energy, environment and global climate have been under high pressures. Battery-powered electric vehicles (EVs) have received wide attention for less-pollution during use, low noise and high energy efficiency. However, the wide-spread use of EVs is still hindered by limited battery capacity and relatively short cruising range. It is of significance to help drivers plan the optimal energy-efficient routes, estimate the cruising ranges or find the recharging stations timely. Establishing EV energy consumption estimation models is the base of route planning, nevertheless, the existing research ignores the impact of the driving cycle and traffic information on EV energy consumption and fails to estimate the EV energy consumption in the real traffic network accurately. Therefore, this paper aims to propose EV energy consumption estimation approach in which driving parameters are taken into consideration.First, based on the data collected by the chassis dynamometer test with New European Driving Cycle (NEDC), the impacts of microscopic driving parameters (instantaneous speed and acceleration) and Vehicle Specific Power (VSP) on EV energy consumption rates are fully analyzed.Then, both instantaneous speed and acceleration, or VSP are used as independent variables while polynomial function models and exponential function models are selected as the regression model structures. A set of energy consumption rate models for different operation modes (accelerating, decelerating, cruising and idling) are established. Further, EV energy consumption models using average speed as explanatory variables are established considering that the input parameter is easily obtained from usual road traffic information systems. In order to reflect the impact on energy consumption of microscopic parameters and exclude microscopic parameters from the model, microscopic energy consumption rates of different VSP-Bins are calculated and VSP distributions under different average speeds are analyzed. The variance of EV energy consumption to different average travel speeds is described successfully in these models.Next, according to the floating car data (FCD) collected from the road network in Beijing, the VSP distributions under different average travel speeds for different road types are analyzed, and then the EV energy consumption factor models for different road types are established. The EV energy consumption modeling methods are further improved.Finally, based on the microscopic and mesoscopic EV energy consumption models, cruising range of EV estimation methods are introduced when EVs travel on planned routes according to drivers’ demand. Moreover, the proposed cruising range estimation methods are validated by the tests on road with a real vehicle.