Drive Cycle‐Based Estimation of Energy Consumption for Electric Two‐Wheeler

ABSTRACT The transportation sector is the backbone of the economic growth of any country. However, the heavy dependence of this sector on petroleum fuel is a matter of concern for sustainable development. To address this issue countries are working toward green energy‐based transportation, and among all viable solutions electric vehicles (EVs) are emerging as front runners. Range anxiety is one of the most prominent concerns in EV adoption. The range of a vehicle depends on the energy consumption so it becomes crucial to estimate it very precisely. There are many standard drive cycles such as the New European Driving Cycle (NEDC) and Worldwide harmonized Light‐duty Vehicle Test Cycles (WLTC) which are used for the estimation of energy consumption. However, these standard cycles fail to capture the driving behavior of real traffic. Due to this reason, these standard cycles underestimate the energy consumption compared with actual consumption. For more realistic energy requirement estimations, researchers are focusing on the development of real‐world drive cycles specific to a particular geography. In this paper, a real‐world drive cycle of electric two‐wheeler has been developed for the city of Lucknow, India, and compared with the driving characteristics and energy consumption estimates of WLTC. The energy requirement per km for the Lucknow drive cycle and WLTC are found as 14.89 Wh/km and 11.95 Wh/km, respectively, which indicates per km energy required estimation for LDC is 24.60% higher than WLTC.

Authors

Institutions

Publication Details

Journal
Energy Storage
Published
2024-09-01
DOI
https://doi.org/10.1002/est2.70030
Citations
2
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
0.41
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Drive Cycle‐Based Estimation of Energy Consumption for Electric Two‐Wheeler

Devendra Vashist, B. Pandey
2 citations
Energy Storage
Vehicle emissions and performance
0.41
article

Drive Cycle‐Based Estimation of Energy Consumption for Electric Two‐Wheeler

Devendra Vashist, B. Pandey
article en
2 citations

Abstract

ABSTRACT The transportation sector is the backbone of the economic growth of any country. However, the heavy dependence of this sector on petroleum fuel is a matter of concern for sustainable development. To address this issue countries are working toward green energy‐based transportation, and among all viable solutions electric vehicles (EVs) are emerging as front runners. Range anxiety is one of the most prominent concerns in EV adoption. The range of a vehicle depends on the energy consumption so it becomes crucial to estimate it very precisely. There are many standard drive cycles such as the New European Driving Cycle (NEDC) and Worldwide harmonized Light‐duty Vehicle Test Cycles (WLTC) which are used for the estimation of energy consumption. However, these standard cycles fail to capture the driving behavior of real traffic. Due to this reason, these standard cycles underestimate the energy consumption compared with actual consumption. For more realistic energy requirement estimations, researchers are focusing on the development of real‐world drive cycles specific to a particular geography. In this paper, a real‐world drive cycle of electric two‐wheeler has been developed for the city of Lucknow, India, and compared with the driving characteristics and energy consumption estimates of WLTC. The energy requirement per km for the Lucknow drive cycle and WLTC are found as 14.89 Wh/km and 11.95 Wh/km, respectively, which indicates per km energy required estimation for LDC is 24.60% higher than WLTC.

Energy StorageVol. 6(6)
Manav Rachna International Institute of Research and Studies (IN)
Affordable and clean energy
Openalex Percentile: Top 40%
Vehicle emissions and performance
0.41
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.