Energy saving and emission reduction is the key to improve quality and efficiency, transformation and upgrading of intelligent agricultural machinery and equipment. Hybrid tractor is the key model for the development of the global new energy agricultural machinery and equipment industry, and it is also the key technology path to accelerate the transformation of Chinese agricultural machinery to high-end, intelligent and green. In recent years, domestic and foreign combined with local agricultural production characteristics, market demand-oriented, continued to spawn, iterative new technology and new products, and through multi-scene, multi-level demonstration and application, a complete technology research and development and application system was gradually formed, which accelerated the promotion of product maturity. On the basis of outlining the development history and development characteristics of hybrid tractors, the development status of key technologies in this field was summarized and analyzed from four aspects: design and development, power control, intelligence and test verification, which focused on analyzing the technological differences between domestic and foreign models, and the key issues restricting the development of the field were pointed out. Finally, under the background of policy guidance and technological innovation synergy, it looked forward to the development direction of the hybrid tractor industry from the perspective of agricultural modernization empowered by artificial intelligence, big data and other emerging technologies, and puted forward its future development trend in the optimized design of the whole machine, collaborative optimization and control, special performance test equipment, intelligent operation control and other aspects.

The tractor serving as the core power equipment for achieving agricultural modernization and efficient production, has a technological development level that directly influences the efficiency, cost, and sustainability of agricultural operations. The industry is rapidly evolving toward high-end, intelligent, and green directions, with new power transmission technologies becoming the most critical and dynamic area of innovation in this transformation. A comprehensive review of the current research status of new power transmission technologies for tractors, both domestically and internationally was provided, which systematically addressed the field from three dimensions: theoretical research on new transmission systems, development of key technologies, and industrial applications. It was focused on diverse technical pathways, including power shift transmission, hydro-mechanical continuously variable transmission, pure electric drive systems, as well as diesel-electric hybrid, hydrogen hybrid, and methane hybrid power systems. It delved into the basic structure, working principles, and performance characteristics of these power transmission systems, and the development status of key technologies was analyzed by examining typical tractor products from China and other countries, along with their practical application outcomes and productization paths. The critical bottleneck issues that needed to be overcome in current new power transmission technologies were generalized and summarized, primarily including battery capacity and charging rates, control precision and stability, environmental adaptability of electric drive systems, multi-energy source management, and the production and storage of new energy sources. Finally, it outlined future development trends for new power transmission systems in tractors, proposing deep integration in three major directions: global energy efficiency utilization, full-scenario self-adaptive compatibility, and modular multi-functional expansion.

The development of new energy power equipment for agriculture is of great significance for promoting the green and low-carbon transformation of agriculture, ensuring national food security and achieving agricultural modernization. A systematic review of domestic and international research progress in new power equipment for agricultural was provided. It focused on analyzing the current status and development trends of four major categories of equipment: new energy tractors, new energy micro-tiller, new energy work platforms, and new energy agricultural low-altitude aircraft. In the field of new energy agricultural machinery, tractors are developing in parallel toward pure electric, hybrid, and clean fuel options; new energy micro-tiller are evolving from “pure electric dominance” to “electric and hybrid parallel development and intelligent self-propulsion”. New energy work platforms are advancing along a technical path characterized by “electric drive as the main power source, supplemented by hydrogen/biofuels, and multi-form coordination of wheels, tracks, and wheeled legs”. New energy agricultural low-altitude aircraft are developing along a technical route featuring “electric drive as the main power source, hydrogen energy for extended range”. However, the new energy agricultural equipment industry is currently facing challenges such as inadequate adaptation of core technologies, an incomplete standard testing system, weak industrial chain coordination, lagging infrastructure, and an incomplete market service system. To this end, it was proposed that future efforts should be coordinated across multiple fronts: top-level policy design and standard testing, breakthroughs in key “three-electric” technologies and specialized chassis systems, industrial chain collaboration and pilot-scale validation, energy-supply infrastructure such as fast charging, battery swapping, and hydrogen fuel, and the completion of scenario-based demonstration and service systems. It was suggested to enhance the adaptability and reliability of new energy agricultural machinery to promote the application of electric agricultural machinery.

Tractors are the most widely used power machinery in agricultural production. Conducting durability simulations of tractors under real-world operating conditions through laboratory test benches is of great significance for improving their reliability. A four-column wheel coupling test bench was utilized to explore the whole-machine durability testing methodology for tractors. An operational load acquisition system was established to collect load data under actual working conditions. Accelerated life testing was conducted by using three different identification methods: the time-domain damage retention identification method, the time-frequency analysis-based cumulative power spectral density identification method, and the wavelet transform-based envelope identification method. The effectiveness of these acceleration methods was validated through wheel coupling bench testing. The results indicated that, within the application scenarios and iterative approaches adopted, the time-frequency analysis-based cumulative power spectral density identification method demonstrated superior performance in signal compression, achieving a reduction ratio of 36.37%. The drive load spectra for the wheel coupling test bench were iteratively derived from both the original signal and the three accelerated signals. The loading results demonstrated that when the chassis and cab were selected as test targets, the damage reproduction tendency at designated measurement points was effectively achieved. Under the same test conditions but with different acceleration identification methods, the time-frequency analysis-based cumulative power spectral density identification method showed superior consistency in reproducing chassis damage, while the time-domain damage retention identification method performed better in replicating cab damage.

In response to the issue that traditional communication network cabling methods are unable to meet the requirements of high efficiency, stability and functional expansion for information transmission in autonomous hydrogen fuel cell tractors, a multi-rate control area network (CAN) bus architecture was proposed based on the SAE J1939 protocol and ISO 11783 standard. Firstly, the data flow requirements for sensing, positioning, drive control, etc. were analyzed in combination with the autonomous operation process in the field. Then, using the principle of minimum complexity in graph theory, multiple topologies were compared and a gateway plus three-bus structure was determined. The CAN communication network nodes were divided based on the structure of the autonomous operation hydrogen fuel cell tractor and its working conditions, and the functions of each node were defined. For common network topologies, a mathematical model was established based on graph theory, and the total information volume per second N and the node information volume per second Z of each structure were analyzed and compared. A high-speed and low-speed dual-bus structure was adopted to design the communication network of the autonomous operation hydrogen fuel cell tractor, with bus rates selected as 500 kb/s and 250 kb/s. The communication message and system software design were developed based on the SAE J1939 protocol and ISO 11783 standard. The hardware functions and communication effects of the communication system were tested by using CANoe software and verified on the whole vehicle. The test results of the bus load rate were 28.22%, 19.20% and 22.85%, all below the 50% requirement. These results verified the feasibility and provided a feasible solution for the design of the communication network of autonomous operation hydrogen fuel cell tractors.

Hilly and mountainous areas are important grain production bases in China. The farmlands in these regions are characterized by small plot sizes, steep slopes, and narrow roads. Traditional fuel-driven chassis have disadvantages such as slow power response, inflexible steering, and low levels of intelligence. To address these issues, an electric intelligent chassis suitable for light and simple rice and wheat harvesters was designed. This machine adopted a distributed design to achieve flexible steering and a wide track design to adapt to rice harvesting operations in hilly and mountainous areas. Motion condition analysis was conducted, and the parameter design of the electric drive system and battery system was completed, solving the problem of slow power response of fuel-powered chassis. The software and hardware design of the motion control system was carried out, enabling remote control operation or autonomous navigation of the chassis. Performance tests and operation parameter optimization tests were conducted. Taking the harvesting speed, threshing drum speed, and cleaning fan speed as test factors, and the breakage rate, impurity rate, and loss rate as evaluation indicators, a Box-Behnken test was designed. The results of the Box-Behnken test were analyzed by variance, and a regression model between the evaluation indicators and the test factors was established. With the goal of minimizing the breakage rate, impurity rate, and loss rate, the optimal solution for the harvesting speed, threshing drum speed, and cleaning fan speed was obtained: the harvester's harvesting speed was 0.8 m/s, the threshing drum speed was 1 000 r/min, and the cleaning fan speed was 2 786.15 r/min. Field tests showed that under this condition, the breakage rate was 0.42%, the impurity rate was 4.05%, and the loss rate was 0.87%. The machine operated smoothly during the operation period, and the operation indicators met the standards for mechanized rice and wheat harvesting. The test results indicated that the designed electric intelligent chassis could meet the operational requirements of the harvester.

Aiming to address issues such as low energy utilization efficiency and insufficient speed stability in electric tractor traction operations, an energy-saving control method was proposed based on a four-motor dual-coupled power system (FDPS). The FDPS combined the characteristics of distributed drive for front and rear axles with coupled drive for single axles, supporting single-motor, dual-motor, triple-motor, and quad-motor drive modes. A longitudinal dynamics model for the working unit and a tire-soil interaction model were established, along with motor and transmission system models that characterized the efficiency and dynamic properties of the FDPS. A multi-drive-mode energy-saving control architecture matching traction workload was proposed. The upper layer employed a hybrid penalty function particle swarm algorithm to offline generate FDPS drive mode switching and multi-motor optimal torque distribution rules based on varying demand driving forces and operating speeds. The lower layer integrated a fuzzy PID algorithm to online identify the machine's demand driving force with precision while tracking target operating speeds. A 900-second energy-saving control bench test was conducted by using field-measured traction resistance data. Test results demonstrated that the proposed method reduced energy consumption by 3.76% and lowered the root mean square speed error by 11.1% compared with the average torque distribution control strategy, enhancing the machine's operational economy and speed stability. The proposed power system can serve as a universal power platform, and the energy-saving control method can provide a reference for multi-power-source drive control research in electric tractors.

Aiming to investigate the impact of battery capacity configuration on system efficiency and life cycle cost (LCC) for high-horsepower hybrid tractors, thereby addressing the research gap in battery capacity optimization design for hybrid tractors, taking a 190 kW series hybrid tractor as the research object, an LCC evaluation system encompassing equipment procurement, battery replacement, and fuel consumption was established. A two-level battery capacity optimization method combining enumeration and dynamic programming (DP) was proposed: the outer layer investigated the influence of battery capacity on LCC under time-varying weights of energy and battery prices through global search via enumeration method, while the inner layer employed DP algorithm for optimal control of energy management strategies in hybrid tractors. A tractor simulation platform was developed by using Matlab/Simulink to quantitatively analyze the coupling mechanism between battery capacity and energy management strategies on system efficiency throughout the tractor's lifecycle. Simulation results indicated that within the 2.2~110 A·h battery capacity range, increasing battery capacity benefited fuel consumption reduction and battery lifespan extension; the 24.2 A·h configuration represented the fuel consumption inflection point, beyond which capacity increase yielded minimal efficiency improvement; when battery capacity reached 52.8 A·h, no replacement was required based on cycle life, but the nonlinear battery capacity-LCC relationship showed 22 A·h configuration minimized LCC to 3.909 3 million yuan. The proposed “technical parameters-life cycle cost” optimization framework established theoretical paradigms and provided valuable references for hybrid system design in agricultural machinery.

Aiming at the problems of poor terrain adaptability, inflexible movement and insufficient environmental friendliness of the current power equipment, a four-wheel multi-mode steering electric unmanned agricultural power equipment with an articulated frame and an independently driven steering wheel set was proposed to meet the operational needs of sowing, tillage, plant protection, transportation and other links in facility horticultural agricultural production. Firstly, the overall structure of the power equipment consisted of an articulated frame, an independently driven steering wheel set, a central suspension device and an electronic control system. It supported multiple steering modes, including two-wheel steering, four-wheel steering, on-the-spot steering and crab steering. Next, matching calculations were performed on key components of the power system, such as the drive motor, steering motor, PTO motor, and power battery. Subsequently, the dynamic motion characteristics of the agricultural power equipment under various steering modes were analyzed, and a multi-mode dynamic model was established. Finally, a hierarchical drive control method was applied in the mechatronic control system, and multiple field tests were carried out with driving speed, steering performance, climbing performance, stability of tillage depth, and endurance performance as evaluation indices. The test results showed that the equipment achieved an average driving speed of 9.67 km/h, the minimum turning radius of 1715.5 mm under four-wheel Ackerman steering, the maximum climbing grade was 15°, the coefficient of the tillage depth stability was 94.62%, and the battery runtime was 2.18~2.77 h. The equipment demonstrated excellent steering characteristics, passability, and operational stability, providing theoretical and technical support for the design of advanced small-and medium-sized intelligent agricultural machinery equipment.

In allusion to the efficient vibration energy recovery problem of a wheeled electric tractor, a variable stiffness spring was innovatively integrates into the research team's existing vibration energy feedback device and a method was proposed to match the device's resonance frequency with the road surface excitation frequency, thereby improving energy capture performance. Firstly, the range of road excitation frequency was analyzed based on the road grade and vehicle speed of the electric tractor. Subsequently, a nonlinear 10-degree-of-freedom dynamic model of the variable stiffness vibration energy feedback device was formulated. With the QR decomposition, implicit restart Arnoldi method (IRAM) and adaptive cross approximation algorithm (ACA), the modal frequencies of the device were solved, and the modal evolution law was analyzed by combining these methods with the finite element method. On this basis, the stiffness coefficient of variable stiffness spring was determined, and the frequency matching method for the variable stiffness vibration energy feedback device was proposed. Finally, fixed-frequency and swept-frequency bench tests were conducted to compare the energy capture performance of the fixed and variable stiffness vibration energy feedback devices. The results demonstrated that the variable stiffness spring structure significantly broadened the resonance band of the device, increased the maximum instantaneous output voltage to 52.2 V, and boosted the average output power and electricity generation by 34.4% and 42.8%, respectively, at the same time, it met the vibration reduction requirement for the battery pack. The above research can provide theoretical and technical support for the power supply of electric tractors and it was of great significance to promote the development of its energy-saving technology.