Simulation of Hybrid Vehicle Powertrain with an Advanced Battery Model 2011-28-0069

In the recent years there has been observed an increasing concern about global warming and greenhouse gas emissions. In addition to the environmental issues the predicted scarcity of oil supplies and the dramatic increase in oil price puts new demands on vehicle design. As a result energy efficiency and reduced emission have become one of main selling point for automobiles. Hybrid electric vehicles (HEV) have therefore become an interesting technology for the automotive industries.

HEV are more complicated compared to conventional vehicles due to the fact that these vehicles contain more electrical components such as electric machines, power electronics, electronic continuously variable transmissions (CVT), and embedded powertrain controllers. Advanced energy storage devices and energy converters, such as Li-ion batteries and fuel cells are also considered. Computer simulation is indispensible to facilitate the examination of the vast hybrid electric vehicle design space with the aim to predict the vehicle performance over driving profiles, estimate fuel consumption and the pollution emissions.

There are various types of mathematical models and simulators available to perform system simulation of vehicle propulsion. One of the standard methods to model the complete vehicle powertrain is “backward quasistatic modeling”. In this method vehicle subsystems are defined based on experiential models in the form of look-up tables and efficiency maps. In the present work we have developed a semi-physical battery model that on one side could be simulated fast on the other side include all important physical phenomena in the battery. IEEE standard hardware description language VHDL-AMS has been used to model the battery. We have then coupled this detailed model of the battery with the rest of the vehicle resulting in a series hybrid electric vehicle model.

The work depicts an in-depth modeling methodology for battery with physical reasoning and its integration into hybrid electric vehicle design.