From sport to eco: A case study of driver inputs on electric vehicle efficiency

Sugihara, Claire; Sutton, Katrina; Davis, Adam Wilkinson; Karanam, Vaishnavi; Tal, Gil

doi:10.1016/j.trf.2021.09.007

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…On the other hand, it has been found that drivers do not know much about the performance of an electric vehicle, whether it is a hybrid or not, and they doubt the convenience of changing from one driving mode to another to reduce the energy consumption rate, extending the driving range [13]. Due to this situation, drivers run electric vehicles in non-optimal conditions, wasting energy and lowering vehicle efficiency [14], which is especially significant in hybrid electric vehicles due to the safeguarding of the internal combustion engine that guarantees the continuous operation of the car and ensures the completion of the planned route.…”

Section: Introductionmentioning

confidence: 99%

Battery Management for Improved Performance in Hybrid Electric Vehicles

Armenta-Déu

2024

Vehicles

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This study aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We developed 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 an energy-saving mode and performance improvement. This protocol was applied to a simulation process to predict energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and any 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 performed 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 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.

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Section: Introductionmentioning

confidence: 99%

Battery Management for Improved Performance in Hybrid Electric Vehicles

Armenta-Déu

2024

Vehicles

View full text Add to dashboard Cite

show abstract

“…On the other hand, drivers do not know much about the performance of an electric vehicle, hybrid or not, and doubt the convenience of changing from one driving mode to another to reduce energy consumption rate, extending the driving range [28]. Due to this situation, drivers run electric vehicles in non-optimal conditions, wasting energy and lowering vehicle efficiency [29], which is especially significant in hybrid electric vehicles due to the safeguarding of the internal combustion engine that guarantees the continuous operation of the car and ensures carrying out the planned route.…”

Section: Introductionmentioning

confidence: 99%

Battery Management for Improved Performance in Hybrid Electric Vehicles

Armenta-Déu

2024

Preprint

View full text Add to dashboard Cite

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.

show abstract