Torque ripple in a brushless DC motor (BLDCM) seriously restricts its application in high-performance fields. This paper proposes a commutation torque ripple suppression strategy based on a Zeta converter. The expected output voltage of a Zeta converter that suppresses the commutation torque ripple is obtained, according to the effect of the duty ratio of the Zeta converter on the turn-off phase freewheeling duration and the turn-on phase rising duration, during commutation. Based on the analysis of the dynamic response of the Zeta converter, the Zeta converter is adjusted to ensure that the Zeta converter reaches stability in sufficient time. During the commutation, the output voltage of the Zeta converter is connected to the main circuit to reduce the torque ripple during commutation, and the expected regulated duty cycle of the Zeta converter during the next commutation is calculated to adjust the output voltage of the Zeta converter. Based on this analysis, the experimental results verify the effectiveness of the proposed method.

The traction performance analysis of hydro-mechanical transmission (HMT) tractors is employed to evaluate and optimize the transmission system during the design phase, thereby reducing research and development costs associated with continuously variable tractor transmission systems. However, there is currently no established methodological framework for calculating the traction performance of HMT tractors. To address this gap, this study integrated traditional tractor traction performance calculation equations with a self-developed HMT energy consumption calculation method, thereby developing a traction performance calculation model for HMT tractors. Initially, the principle of the tractor’s hydrostatic power-split transmission system was introduced. Subsequently, mathematical models for calculating transmission system energy consumption and tractor traction performance were established, with key sub-models experimentally validated to ensure the reliability of subsequent results. On this foundation, a calculation method for the traction performance of HMT tractors was proposed. Finally, models before and after energy consumption optimization, as well as models under different road conditions and transmission system configurations, were utilized as comparative models to calculate the traction performance of HMT tractors under various settings. The results indicate that energy optimization of HMT not only improves the transmission performance and reduces fuel consumption of HMT tractors, but also enhances the matching capability of HMT tractors with farm tools under high traction efficiency. Additionally, road conditions significantly impact the traction performance of HMT tractors. In wheat stubble fields, the tractor’s traction performance is substantially lower than on standard roads, with a maximum traction force decrease of 40.8% at a slip rate of 30%.

Thermoelectric generators are high-profile energy conversion devices that can convert heat energy into electricity. In this study, a novel 1D resistance model was established to evaluate the performance of a segmented thermoelectric generator (STEG) with variable properties, and the genetic algorithm was adopted to optimize the performance. Then, influence factor analysis, multi-parameter optimization, and sensitivity analysis for an STEG couple were conducted. The results showed the great influence of geometric sizes on performance. Moreover, the optimal length ratio between the length of the high-temperature segment and the total leg length increased when the temperature difference (ΔT) was raised, but it remained unchanged as the convective heat transfer coefficient (h) changed. Furthermore, the ratio of the leg length to its cross-sectional area is affected by thermal conditions and the length ratio, while the cross-sectional area ratio between P- and N-type thermoelectric legs was not affected by the convective heat transfer coefficient. Under the conditions of ΔT = 300 K and h = 2000 W/m²K, the maximum power increased by 11.02%. Finally, the global sensitivity analysis found that material properties, especially the Seebeck coefficient, dominate the influence on optimal power. These results could contribute to the optimal design of STEGs.