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Modeling and Simulation of Electric and Hybrid Vehicles

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INVITED PAPER Modeling and Simulation of Electric and Hybrid Vehicles Tools that can model embedded software as well as components, and can automate the details of electric and hybrid vehicle design, need to be developed. By David Wenzhong Gao, Senior Member IEEE, Chris Mi, Senior Member IEEE, and Ali Emadi, Senior Member IEEE ABSTRACT | This paper discusses the need for modeling and simulation of electric and hybrid vehicles. Different modeling methods such as physics-based Resistive Companion Form technique and Bond Graph method are presented with powertrain component and system modeling examples. The modeling and simulation capabilities of existing tools such as Powertrain System Analysis Toolkit (PSAT), ADvanced VehIcle …show more content…

Advances in electronic design tools have validated Moore’s law (as applied to the complexity of integrated circuits) and have helped achieve amazing standards in computing power while simultaneously decreasing costs. For designers of automotive systems to duplicate and manage similar levels of complexity, design tools that automate the Vol. 95, No. 4, April 2007 | Proceedings of the IEEE 729 0018-9219/$25.00 Ó 2007 IEEE Authorized licensed use limited to: University of Michigan Library. Downloaded on January 15, 2009 at 22:22 from IEEE Xplore. Restrictions apply. Gao et al.: Modeling and Simulation of Electric and Hybrid Vehicles low-level details of the design process need to be developed [3], [4]. Depending on the level of details of how each component is modeled, the vehicle model may be steadystate, quasi-steady, or dynamic [5]–[15]. For example, the ADVISOR [5], [6] model can be categorized as a steadystate model, the PSAT [7] model as quasi-steady one, and PSIM [8] and Virtual Test Bed (VTB) [9] models as dynamic. On the other hand, depending on the direction of calculation, vehicle models can be classified as forwardlooking models or backward facing models [5]. In a forward-looking model, vehicle speed is controlled to follow a driving cycle during the analysis of fuel economy, thus facilitating controller development. The main advantage of employing a steady-state model or quasi-steady model is fast computation, while the

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