978-1-5090-2320-2/16/$31.00 ©2016 IEEE Battery Management System (BMS) Simulation Environment for Electric Vehicles Luca Buccolini, Adrianna Ricci, Cristiano Scavongelli, Giuseppe DeMaso-Gentile, Simone Orcioni, Massimo Conti Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Ancona, Italy Abstract— The wide diffusion of Full and Hybrid Electric Vehicles is stimulating research on electric energy storage systems and Battery Management Systems (BMS). The Battery management system must ensure many complex features such as charge control, battery-capacity monitoring, remaining run-time information and charge-cycle counting. An optimization of the BMS can allow an improvement on security of the vehicle, performance of the engine, energy optimization and extension of the life of the battery. The main objective of this work is to develop a simulation environment based on SystemC to design and optimize the Battery Management System including a lithium-ion battery model and CAN communication interface. The BMS has been validated using real-world scenarios and data. Keywords— BMS, battery, SystemC, CAN I. INTRODUCTION After years of discussions, scientific evidence shows that climate change is occurring, mainly due to human activities. Worldwide public opinion and decision makers are moving in the direction of doing something to overcome this problem. Global warming is mainly due to the emissions of CO 2 caused by the combustion of fossil fuels (coal, natural gas, and oil) for energy production and transportation. Producing more energy from renewable sources is a way to reduce carbon emissions. The combustion of fossil fuels to transport people and goods (highway vehicles, air travel, marine transportation, and rail) is the one of the largest source of CO 2 emissions in industrialized countries. As an example, the ‘European Green Cars Initiative’ work program concentrates on research on electric and hybrid vehicles with the aim of strong reduction in CO 2 emissions. On the basis of these considerations, a lot of research, prototypes and commercial products of low emission engine for transportation are now available. Full Electric Vehicles (FEVs), also called Plug-in Electric Vehicles (PEVs), are solely powered by batteries and electric motors. Nowadays the FEVs have some serious limitations, such as the high batteries cost, the limited driving range, the high recharge time. In order to make hybrid, plug-in hybrid and fully electric vehicles fit for the mass market, the energy density and efficiency of battery packs need to increase. Besides research on advanced electro- chemistries, the integration of batteries primary cells into battery packs has great role to play. Furthermore the impact of the recharge of FEV on the grid and the lack of an adequate electrical infrastructure for charging purposes is a relevant aspect to be faced [1-3]. Many aspects must be faced for the energy optimization in a FEV, for example: • system integration of electric machines with transmissions; • optimization of energy recovery with the integration of braking systems; • integration of power electronics with battery charging functions; • creation of models the components (motor, batteries, inverters, fuel-cells) that can be used for design, simulation, diagnosis and testing. • creation of a simulation environment for the simulations of the electric digital-analog components and the mechanical and chemical components In this context, an aspect to be faced is the battery monitoring system. If we want to make a FEV reliable, we must be able to control the battery state of charge, that tells us if we need to stop and recharge the car, the battery state of health, that tells us if the battery is still good or if we need to buy a new one, and the battery temperature, that must be kept inside a well-defined range of safe values. In a FEV, the battery management system (BMS) controls the state and utilization of the battery. In literature several BMS simulation models exist [4-9]. They are mainly related to the model of the battery and the characterization of model itself. The battery model is fundamental to estimate the state of charge. But the models used in the literature cannot be easily integrated in the enviroment used for system level design. SystemC is a consolidated design language and environment, based on C++, used for system level description of electronic systems. SystemC is very well suited to the design and refinement of HW/SW systems from system-level down to register-transfer-level (RTL). However, for a broad range of applications, the digital parts of an electronic system closely interact with the analog chimical and mechanical parts and thus with the continuous-time environment. SystemC-WMS [10] has been used for this type of applications with digital and analog analog parts for example a Bluetooth transceiver, modeling of a wireless channel and solid state dimming [11- 12]. In this work, we present, in Section II a SystemC model of the BMS that can be easily interfaced with other hardware models such as for example the CAN bus. To prove the effectiveness of our model, in Section III we report the application of the model in several real driving test scenarios.