Usable time estimation and suitable battery selection for electric tractor considering agricultural operational load

This study estimates battery usable time and discharge rates, and selects a suitable battery for a single-motor electric tractor using dynamometer tests and rotary tillage at L-slow, L-fast, and M-slow gear stages. The dynamometer results were validated for rotary tillage to determine a suitable battery for full-day (8 h) operations. In dynamometer tests, battery power consumption for light, medium, and heavy-duty loads was 6.25, 8.76, and 14.51 kW, resulting in usable times of 3.00, 2.33, and 1.25 h, respectively. Rotary tillage results confirmed similar battery consumption trends, validating the dynamometer-based estimation. For continuous 8-hour operations, a 900 Ah battery (64.8 kWh) was satisfied at the gear stage of L-fast for rotary tillage. It was observed that battery mass and volume increased proportionally with energy density. Results confirmed that higher energy storage required a larger and heavier battery pack for full-day operations. The battery energy density of 64.8 kWh (900 Ah) would be suitable with practical weight and space limitations to perform full-day operations. The limitation is that traction efficiency, slip ratio, and effective field capacity were not considered for suitable gear stage selection. However, we believe that this study provides a feasible technique for battery selection in real agricultural scenarios, offering practical insights for electric tractor manufacturers.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-10-21
DOI
https://doi.org/10.1038/s41598-025-20517-5
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Usable time estimation and suitable battery selection for electric tractor considering agricultural operational load

Hyeon-Ho Jeon, Wan-Soo Kim, Yeon-Soo Kim, Seung-Min Baek et al.
Scientific Reports
Advanced Battery Technologies Research
article

Usable time estimation and suitable battery selection for electric tractor considering agricultural operational load

Hyeon-Ho Jeon, Wan-Soo Kim, Yeon-Soo Kim, Seung-Min Baek, Seung-Yun Baek, Md. Abu Ayub Siddique, Cheng‐Fu Yang, Yong‐Joo Kim, Namsik Chung
article en

Abstract

This study estimates battery usable time and discharge rates, and selects a suitable battery for a single-motor electric tractor using dynamometer tests and rotary tillage at L-slow, L-fast, and M-slow gear stages. The dynamometer results were validated for rotary tillage to determine a suitable battery for full-day (8 h) operations. In dynamometer tests, battery power consumption for light, medium, and heavy-duty loads was 6.25, 8.76, and 14.51 kW, resulting in usable times of 3.00, 2.33, and 1.25 h, respectively. Rotary tillage results confirmed similar battery consumption trends, validating the dynamometer-based estimation. For continuous 8-hour operations, a 900 Ah battery (64.8 kWh) was satisfied at the gear stage of L-fast for rotary tillage. It was observed that battery mass and volume increased proportionally with energy density. Results confirmed that higher energy storage required a larger and heavier battery pack for full-day operations. The battery energy density of 64.8 kWh (900 Ah) would be suitable with practical weight and space limitations to perform full-day operations. The limitation is that traction efficiency, slip ratio, and effective field capacity were not considered for suitable gear stage selection. However, we believe that this study provides a feasible technique for battery selection in real agricultural scenarios, offering practical insights for electric tractor manufacturers.

Scientific ReportsVol. 15(1)
Chungnam National University (KR), Kyungpook National University (KR), Quality and Reliability (Greece) (GR), National University College (PR), Pusan National University (KR)
Ministry of Agriculture, Food and Rural Affairs
Openalex Percentile: Top 67%
Advanced Battery Technologies Research
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.