Version 1
: Received: 9 April 2024 / Approved: 10 April 2024 / Online: 11 April 2024 (12:50:55 CEST)
How to cite:
Armenta-Déu, C. Battery Management for Improved Performance in Hybrid Electric Vehicles. Preprints2024, 2024040747. https://doi.org/10.20944/preprints202404.0747.v1
Armenta-Déu, C. Battery Management for Improved Performance in Hybrid Electric Vehicles. Preprints 2024, 2024040747. https://doi.org/10.20944/preprints202404.0747.v1
Armenta-Déu, C. Battery Management for Improved Performance in Hybrid Electric Vehicles. Preprints2024, 2024040747. https://doi.org/10.20944/preprints202404.0747.v1
APA Style
Armenta-Déu, C. (2024). Battery Management for Improved Performance in Hybrid Electric Vehicles. Preprints. https://doi.org/10.20944/preprints202404.0747.v1
Chicago/Turabian Style
Armenta-Déu, C. 2024 "Battery Management for Improved Performance in Hybrid Electric Vehicles" Preprints. https://doi.org/10.20944/preprints202404.0747.v1
Abstract
The work aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We develop a specific protocol for managing battery use and optimizing the energy consumption rate to achieve this goal. The protocol automatically controls the driving operation, avoiding incompatible driving patterns with energy-saving mode and performance improvement. The protocol is submitted to a simulation process to predict the energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and route conditions since it uses vehicle mass, drag and rolling coefficients, and road slope as variable parameters to determine the minimum energy consumption rate. We run experimental tests to validate the simulation data and the proposed protocol. Furthermore, the protocol applies to variable starting vehicle speeds, from 10 to 50 km/h, corresponding to the current driving patterns, sport, normal, and eco, set up by car manufacturers. A reduction of 10% in vehicle speed in urban and peripheral routes achieves a minimum energy rate, enhancing battery management. Current vehicle speed shows a deviation from optimum management of 18% while applying the vehicle speed reduction limits the deviation to 0.2%. Experimental results show a good agreement with simulation data with 94% accuracy. We tested the protocol for urban and peripheral routes with maximum vehicle speed limits of 60 and 90 km/h.
Keywords
Hybrid Electric Vehicle; Battery Management; Performance Enhancement; Energy consumption rate; Vehicle Speed
Subject
Engineering, Automotive Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
