An Eco-Driving Technique for Energy Aware Driving With an Electric Vehicle

Driving habits of individual drivers have shown to have a strong impact on energy consumption and range of electric vehicles. Eco-driving is a popular procedure for improving the range by manipulating multiple factors such as the car speed or providing corrective suggestions related to the route. An optimized eco-driving can be considered for minimizing the energy consumption, taking into account the driving conditions and situations. In this contribution, a driving pattern recognition is considered wherein two indices namely, driving condition index (DCI) and driving situation index (DSI) are used to characterize a certain pattern. Combinations of DCI and DSI are mapped into a representative driving pattern (RDP) matrix. Based on the chosen RDP values, a reference speed for the vehicle is generated and corresponding PI controller parameters tuned within a driver model to realize eco-driving. The eco-driving strategy is optimized for minimization of energy consumption with the help of Pontryagin's minimum principle (PMP) within a constrained action space defined by the DCI and DSI indices. This novel feature allows an event specific optimal solution to be generated rather than a time specific solution. The simulation results prove the efficiency of the optimized eco-driving in preserving the battery energy and charge. It also shows the selection of representative patterns corresponding to actual driving based on DCI and DSI indices.