Artigo Acesso aberto

Development of a Driver-in-the-Loop Simulation to Evaluate the Performance to Energy Trade-Off of Active Dynamics Systems on an Electric Race Car

2022; Volume: 1; Linguagem: Inglês

10.4271/2022-01-5040

ISSN

2688-3627

Autores

Georgios Chrysakis, Jonathan Vogel, Kamyar Nikzadfar,

Tópico(s)

Vehicle emissions and performance

Resumo

Automotive industry interest in renewable propulsion technology has led to a surge of investment in electric-only motorsport categories as a technological test bed.Electrification has enabled easier implementation of active vehicle dynamics control systems to improve performance and drivability, but limitations in battery technology create significant constraints which force a compromise between efficiency and performance.In this paper, four different control systems -Automatic Rear Steering (ARS), Drag Reduction System (DRS), Semi-Active Suspension (SAS), and Torque Vectoring (TV) -are tested in various configurations and combinations with the aim of characterizing their performance to energy consumption trade-offs in an electric Formula Student vehicle.A Driver-in-the-Loop (DiL) simulator was developed using Cruden Panthera along with a multibody Simulink vehicle model to capture the effects of drivability on vehicle performance.Vehicle configurations were tested using a combination of open and closed loop driving manoeuvres, measuring performance indicators to capture absolute performance, power consumption and driver workload.TV was the most effective at improving vehicle performance, but also incurred the largest energy cost.ARS was also found to improve performance by a lesser degree but brought the greatest improvement to drivability.DRS improved straight line performance and energy consumption at the expense of cornering performance and driver workload.SAS improved steady state cornering performance but had minimal effect on transient manoeuvres to justify its energy cost and complexity.Using TV, DRS and ARS in conjunction was found to be the optimal configuration by quantifiably improving driver workload, lap time performance, and power consumption over the baseline vehicle.

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