Title
A SystemC-AMS Framework for the Design and Simulation of Energy Management in Electric Vehicles.
Abstract
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.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2900505
IEEE ACCESS
Keywords
Field
DocType
Cyber-physical systems,design-time optimization,electric vehicles,electrical energy system,SystemC-AMS
Energy storage,Automotive engineering,Energy management,Renewable energy,SystemC AMS,Computer science,Electric potential energy,Driving range,Cyber-physical system,Dimensioning,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Yukai Chen1176.98
Donkyu Baek2177.62
Jaemin Kim3346.84
Santa Di Cataldo47610.82
Naehyuck Chang51985185.85
Enrico Macii62405349.96
Sara Vinco7248.59
Massimo Poncino846057.48