Simulation of Real Driving Cycles of Electric Cars in Laboratory Conditions

Kucera, Lubos; Gajdosik, Tomas; Gajdac, Igor; Mruzek, Martin; Tomasikova, Maria · 2017 · DOAJ

DOI: 10.26552/com.C.2017.2A.42-47

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Summary

This study addresses the challenge of range anxiety in electric vehicles (EVs) by investigating whether specific driving styles can optimize energy consumption and extend driving range. The research focuses on simulating real-world traffic conditions in a controlled laboratory environment to analyze the energy balance of the Edison EV. The primary motivation is to determine if optimizing driving behavior, particularly through acceleration and coasting strategies, can improve the efficiency of the vehicle’s powertrain compared to steady-state driving. The experimental methodology utilized a MAHA MSR 1050 single roller dynamometer to simulate driving cycles for the Edison EV. Researchers first established driving resistance coefficients (rolling resistance and air resistance) through coast-down tests, deriving a polynomial equation to describe resistance relative to speed. These coefficients were compared with those of standard vehicles like the Mitsubishi i-Miev and Nissan Leaf. The study then simulated two distinct driving cycles over a distance of 2.4 km: a steady ride cycle and an experimental "UP-DOWN" cycle. The UP-DOWN cycle involved accelerating from 45 km/h to 55 km/h followed by a free-wheel coasting phase back to 45 km/h, designed to leverage the EV’s ability to recuperate kinetic energy and operate within higher efficiency zones of the drive map. Data from the vehicle’s battery management system and converter were logged to evaluate energy consumption. The results indicated that while the UP-DOWN cycle achieved a powertrain efficiency of 62%—more than 10% higher than the steady ride cycle—it did not reduce total energy consumption from the battery. Both cycles consumed 0.33 kWh from the battery. However, the energy required at the tires differed significantly: the UP-DOWN cycle required 0.21 kWh, whereas the steady ride required only 0.17 kWh. This discrepancy arose because the UP-DOWN cycle demanded more energy to overcome rolling resistance during acceleration phases, which offset the gains from efficient coasting. Consequently, the study concluded that this specific UP-DOWN driving style does not extend the driving range under normal traffic conditions. Additionally, the researchers demonstrated that measured dynamometer data could be effectively used to create realistic engine subsystem models in Simscape Driveline software for further component development. The significance of this work lies in its detailed analysis of EV efficiency maps and the validation that certain intuitive driving optimizations may not yield range benefits due to increased resistive losses. The findings suggest that autonomous management systems must account for these complex energy balances to maximize efficiency. Furthermore, the study provides a validated methodology for using laboratory measurements to create accurate simulation models for EV transmission components, supporting future research in electromobility and autonomous driving control strategies.

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• simulator validity fidelity