A SystemC-AMS Framework for the Design and Simulation of Energy Management in Electric Vehicles
| Autor: | Santa Di Cataldo, Massimo Poncino, Donkyu Baek, Jaemin Kim, Yukai Chen, Sara Vinco, Enrico Macii, Naehyuck Chang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Energy management Computer science 020209 energy 02 engineering and technology Automotive engineering Energy storage design-time optimization Range (aeronautics) 0202 electrical engineering electronic engineering information engineering General Materials Science Dimensioning electric vehicles Cyber-physical systems electrical energy system SystemC-AMS business.industry Electric potential energy General Engineering 020202 computer hardware & architecture Power (physics) Renewable energy lcsh:Electrical engineering. Electronics. Nuclear engineering business lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 25779-25791 (2019) |
| ISSN: | 2169-3536 |
| Popis: | Driving range is one of the most critical issues for electric vehicles (EVs): running out of battery charge while driving results in serious inconvenience even comparable to a vehicle breakdown, as an effect of long fuel recharging times and lack of charging facilities. This may discourage EVs for current and potential customers. As an effect, the dimensioning of the energy subsystem of an EV is a crucial issue: the choice of the energy storage components and the policies for their management should be validated at design time through simulations, so to estimate the vehicle driving range under reference driving profiles. Thus, it is necessary to build a simulation framework that considers an EV power consumption model that accounts for the characteristics of the vehicle and the driving route, plus accurate models for all power components, including batteries and renewable power sources. The goal of this paper is to achieve such an early EV simulation, through the definition of a SystemC-AMS framework, which models simultaneously the physical and mechanical evolution, together with energy flows and environmental characteristics. The proposed solution extends the state-of-the-art framework for the simulation of electrical energy systems with support for mechanical descriptions and the AC domain, by finding a good balance between accuracy and simulation speed and by formalizing the new information and energy flows. The experimental results demonstrate that the performance of the proposed approach in terms of accuracy and simulation speed w.r.t. the current state-of-the-art and its effectiveness at supporting EV design with an enhanced exploration of the alternatives. |
| Databáze: | OpenAIRE |
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