Hybrid Electric Rice–Wheat Combine Harvesters for Low-Carbon and Intelligent Harvesting: A Review

Rice–wheat combine harvesters face coupled traction and material-processing loads whose variability complicates energy saving without reducing throughput or harvest quality. This review connects five perspectives: intelligent sensing, electrified actuation, hybrid powertrain architecture, field-condition prediction, and energy management. It examines interfaces under common quality and battery energy boundaries. Forward crop sensing, feed-rate monitoring, and component-load observation provide complementary information, while independent electric drives make drum, fan, and sieve settings more controllable. Series, parallel, and power-split architectures offer different compromises between controllability, conversion losses, packaging, and sustained-load performance. Direct evidence remains limited: one field prototype reported 19.5% lower fuel consumption than a conventional harvester, a study-specific result that does not establish a general saving range. Evidence from tractors and other vehicles supports transferable methods but cannot replace rice–wheat validation. A comparison matrix examines rule-based, instantaneous, optimal, predictive, and learning-based energy management. The framework couples fuel use and clean-grain throughput with loss, breakage, impurity, and state-of-charge constraints, and outlines life-cycle cost and carbon accounting. It is methodological rather than a new numerical assessment. The priorities are synchronized field duty cycles, uncertainty-aware coordination, thermal and fault validation, and comparisons across sites and seasons. The synthesis supports powertrain design and controller development for more energy-efficient and intelligent harvesting.

Authors

Institutions

Publication Details

Journal
Agriculture
Published
2026-09-30
DOI
https://doi.org/10.3390/agriculture16192126
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Hybrid Electric Rice–Wheat Combine Harvesters for Low-Carbon and Intelligent Harvesting: A Review

Zhihao Zhu, Lizhang Xu, Xiaoxue Du
Agriculture
Electric and Hybrid Vehicle Technologies
article

Hybrid Electric Rice–Wheat Combine Harvesters for Low-Carbon and Intelligent Harvesting: A Review

Zhihao Zhu, Lizhang Xu, Xiaoxue Du
article en

Abstract

Rice–wheat combine harvesters face coupled traction and material-processing loads whose variability complicates energy saving without reducing throughput or harvest quality. This review connects five perspectives: intelligent sensing, electrified actuation, hybrid powertrain architecture, field-condition prediction, and energy management. It examines interfaces under common quality and battery energy boundaries. Forward crop sensing, feed-rate monitoring, and component-load observation provide complementary information, while independent electric drives make drum, fan, and sieve settings more controllable. Series, parallel, and power-split architectures offer different compromises between controllability, conversion losses, packaging, and sustained-load performance. Direct evidence remains limited: one field prototype reported 19.5% lower fuel consumption than a conventional harvester, a study-specific result that does not establish a general saving range. Evidence from tractors and other vehicles supports transferable methods but cannot replace rice–wheat validation. A comparison matrix examines rule-based, instantaneous, optimal, predictive, and learning-based energy management. The framework couples fuel use and clean-grain throughput with loss, breakage, impurity, and state-of-charge constraints, and outlines life-cycle cost and carbon accounting. It is methodological rather than a new numerical assessment. The priorities are synchronized field duty cycles, uncertainty-aware coordination, thermal and fault validation, and comparisons across sites and seasons. The synthesis supports powertrain design and controller development for more energy-efficient and intelligent harvesting.

AgricultureVol. 16(19)
Jiangsu University (CN), Changzhou Institute of Technology (CN)
Responsible consumption and production
Openalex Percentile: Top 20%
Electric and Hybrid Vehicle Technologies
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.

Hybrid Electric Rice–Wheat Combine Harvesters for Low-Carbon and Intelligent Harvesting: A Review — Zhihao Zhu, Lizhang Xu, et al. · Agriculture (2026) | TGRS Research Map | TGRS