Environment-Based Energy Optimization in Toyota Prius for Improved Battery Life and Range
Andrew Chemistruck and Ahmad Bahai
Environment plays a huge role in fuel economy of light-duty passenger vehicles as can be seen in the different fuel economy ratings from the EPA. Our goal is to produce an accurate model for the impact of environment—traffic signals, traffic, road surface conditions, etc—on fuel economy. To validate our model, we are collecting data from a highly instrumented Toyota Prius running through a set of tests designed to extract important environmental impacts on fuel economy. With this model, it will be clear if there are control system improvements that can be made to further enhance city MPG. One key area of interest is multi-signal light energy optimization. Using DSRC enabled traffic signals, we believe that longer time scale events can be scheduled during more optimal times to improve overall system efficiency. Most control algorithms in vehicles typically impose current limits on the battery system. We are looking into a more accurate model of the battery to determine if there are any aging effects that can be avoided by optimally tailoring the current profile to enhance battery life.