Driving Pattern Generation for Customized Energy Control Strategy in Hybrid Electric Vehicle Applications.

摘要

The Driving pattern is unique for each driver when driving on the same route. It's like one's signature that can be used to describe a driver's driving behavior. The driving pattern can be generated from historical driving curves. The driving curves may be different each time when someone is driving on the same route, however, the shapes will be similar. Using the weighted arithmetic mean (WAM) method to find the best pattern based on historical driving records is a way to help the embedded computer to control the Hybrid Electric Vehicle (HEV) Energy system. Using one's driving pattern to customize energy control strategy can be a practical way to optimize the vehicle's efficiency and performance. Once the HEV owners selected their favorite driving modes, for example, to achieve the goal of higher fuel efficiency or achieve longer lifespan of critical components, the embedded computer will maintain the vehicle based on drivers' driving behaviors. Hence, drivers can focus on driving in their most comfortable way, rather than distraction from reading speedometer, engine tachometer, or energy monitor to adjust their driving behavior just to obtain a better number of "miles per gallon" (MPG).