MRI
MRI India Journals Vol. 9 No. 1 (2020)

Performance Evaluation of Hybrid Electric Vehicle Powertrain Systems

Authors

  • Aurelio Ben- Mizrahi Department of Technology and Innovation Management, Shiraz College of Systems and Management, Iran

Keywords:

hybrid electric vehicle powertrain performance evaluation energy management regenerative braking

Abstract

Hybrid electric vehicle (HEV) performance depends on the interaction of powertrain topology, component efficiency, regenerative braking, battery utilization, and supervisory energy management. This paper presents a compact and reproducible methodology for evaluating series, parallel, and power-split HEV powertrains under identical driving demand. The method combines a longitudinal vehicle model with quasi-static energy conversion models, a charge-sustaining supervisory control layer, and common key performance indicators covering equivalent fuel consumption, regenerative energy recovery, cycle-level fuel-to-wheel efficiency, traction capability, and battery state-of-charge constraints. A representative 1500 s urban-highway composite profile is used only as an illustrative case study; it is not presented as regulatory or experimental test data. Under the stated assumptions, the illustrative power-split system produced the lowest equivalent fuel use, followed by the parallel and series configurations. The main contribution is not a claim of vehicle certification performance, but a step-by-step evaluation framework that can be implemented in MATLAB/Simulink, ADVISOR, AVL Cruise, GT-SUITE, or an equivalent simulation environment and subsequently validated using chassis-dynamometer or on-road measurements.

 

Downloads

Published

2020-04-20

How to Cite

Mizrahi, A. B.-. (2020). Performance Evaluation of Hybrid Electric Vehicle Powertrain Systems . International Journal on Mechanical Engineering and Robotics, 9(1), 15–20. Retrieved from https://journals.mriindia.com/index.php/ijmer/article/view/4548

Issue

Section

Articles

Similar Articles

<< < 1 2 3 4 5 6 > >> 

You may also start an advanced similarity search for this article.