An Electric Vehicle Simulator for Realistic Battery Signals Generation from Data-Sheet and Real-World Data

EasyChair Preprint no. 10030

Abstract

Electric vehicles (EVs) have been globally recognized as a reliable alternative to fossil fuel vehicles. The core component of an electric vehicle is its rechargeable battery pack, and Lithium-ion battery (LIB) cells are currently the dominating technology in battery pack design. This game-changing technology pushes toward the investigation of new ideas to improve the offered services.
However, there still needs to be large-scale publicly available EV data to investigate and distribute effective solutions to monitor the conditions of the EV's battery pack.
Hence, we propose an EV simulator that generates EV battery pack internal signals starting from the input driving cycle. The simulated data resemble the behavior of a multi-cell EV battery pack undergoing the user's utilization of the EV. The simulated data include vehicle speed, voltage, current, State of Charge (SOC), and internal temperature of the battery pack. The virtual-EV model simulator, including the battery pack subsystem, has been tuned using real-world EV data sheet information. The battery pack embeds thermal and aging models for further realism, influencing the output signals given the environmental temperature and the battery's State of Health (SOH). The data generated by the virtual-EV simulator have been validated with real EV data signals sampled by an equivalent real-world EV. The data comparison yields a minimum R² value of 0.94 and an Root Mean Squared Error not higher than 2.74 V for the battery pack's voltage and SOC, respectively.

Keyphrases: Battery, EV, simulation, SOH

@Booklet{EasyChair:10030,
  author = {Raimondo Gallo and Alessandro Aliberti and Edoardo Patti and Gianluca Bussolo and Paolo Tosco and Marco Zampolli and Rémi Jaboeuf},
  title = {An Electric Vehicle Simulator for Realistic Battery Signals Generation from Data-Sheet and Real-World Data},
  howpublished = {EasyChair Preprint no. 10030},

  year = {EasyChair, 2023}}