Crow search algorithm (CSA) is a new type of swarm intelligence optimization algorithm proposed by simulating the crows’ intelligent behavior of hiding and retrieving food. The algorithm has the characteristics of simple structure, few control parameters, and easy implementation. Like most optimization algorithms, the crow search algorithm also has the disadvantage of slow convergence and easy fall into local optimum. Therefore, a crow search algorithm based on improved flower pollination algorithm (IFCSA) is proposed to solve these problems. First, the search ability of the algorithm is balanced by the reasonable change of awareness probability, and then the convergence speed of the algorithm is improved. Second, when the leader finds himself followed, the cross-pollination strategy with Cauchy mutation is introduced to avoid the blindness of individual location update, thus improving the accuracy of the algorithm. Experiments on twenty benchmark problems and speed reducer design were conducted to compare the performance of IFCSA with that of other algorithms. The results show that IFCSA has better performance in function optimization and speed reducer design problem.

Electric vehicles use wireless energy transmission to obtain energy, which can effectively avoid the shortcomings of traditional methods. As the carrier of radio energy transmission and reception, the high temperature of the coil triggers the degradation of wireless transmission performance and the aging of the coil, which may cause fire and other safety problems in serious cases. This paper studied the temperature distribution of the magnetically coupled coil model for electric vehicles. Based on the study of the basic law of heat transfer, the coil model was established using ANSYS software, and the boundary conditions and relevant parameters were set. After many simulation experiments and comparisons, it was finally determined that the transmitting coil and the receiving coil were the same sizes, the inner diameter of the coil was 100 mm, the outer diameter of the coil was 181 mm, and the coupling distance between the transmitting coil and the receiving coil was set to 60 mm. Coil models were simulated and analyzed using different materials. The simulation results show that after 30 min of system operation, the material chosen from the temperature range may have been gold, silver, copper, or aluminum, but from the comprehensive consideration of cost and performance, the material of the coil in the model was finally set to copper. Copper was the best material; its temperature maximum was 74.952 °C and lower than the safety value of 80 °C. It is hoped that this study will provide a reference for wireless charging coil design.

The article discusses a wavelet-based approach for recognizing sugarcane stem nodes in order to improve pre-cut sugarcane planting technology, beginning with sugarcane form characteristics that permit automated sugarcane seed production. The location signal is collected by the acceleration and thin-film piezoelectric sensors and then decomposed into the tenth, eleventh, and twelfth layers using the Daubechies tight-branch wavelet. After capturing the signal, it is reconstructed and superimposed to capture the stem node region’s features using the default threshold technique. A multi-sensor fusion approach is developed based on a weighted average and a Kalman filter to confirm the experiment’s validity. The weighted average process produces an average value that is 0.3512 mm off from the experimentally observed data average. The discrepancy between the Kalman filter method’s anticipated average value and the empirically determined average error is 0.5778 mm. To facilitate the investigation, 175 sugarcane samples with intermediate length processing are used. The detecting position system is determined experimentally after extensive experimental research and diligent examination. On average, the standard deviation is 0.494 mm, while the maximum value is 9.99 mm. 99.63 percent of cane seed samples are detected, with an error rate of 0.37 percent and a response time of 0.25 seconds. The proposed technology is conceptually feasible and achievable, and it can provide a reference for the development of automated cane seed pre-cutting machinery to give its contribution to agricultural production.

The topology and parameter characteristics of the wireless energy transmission system are the main factors affecting the system’s performance. A series–parallel–series–parallel (spsp) topology for magnetically coupled wireless energy transmission is proposed to address the problems of low efficiency and low output power when transmitting electrical energy in the conventional magnetically coupled topology. The spsp topology is compared with the conventional topology based on circuit theory, and the two structures are modeled, characterized, and verified in detail. Simulations and tests are performed for the transmission conditions, an improved Gray Wolf optimization algorithm is proposed, and a physical system is built. Experiments show that the spsp structure is superior near the designed circuit parameters when the network works in a resonant state. The improved Gray Wolf optimization algorithm is then used to find the optimal parameters, and the transmission efficiency reaches 90.53%, which effectively improves the transmission performance of the system. The established physical system utilizes the optimized parameters for coil structure and coil offset experiments, and the average transmission efficiency is 83.75%, with an error of 6.78% calculated by data measurement. The rationality of the proposed structure and the correctness of the simulation parameter design method are verified, and it is hoped that the proposed system and circuit structure in this paper will provide a reference for the design of a magnetically coupled wireless energy transmission system.

To improve the transmission efficiency and output power of a magnetically coupled resonant wireless energy transmission system, this paper proposes a multi-objective optimization method based on the analytical expression and the improved NSGA-II algorithm. First, the analytical expressions of the electrical and performance parameters in the magnetically coupled resonant mechanism are derived. On this basis, the mathematical model of the multi-objective optimization of the magnetically coupled mechanism is established, with the size, many turns, and wire diameter of the transmitting and receiving coils in the magnetically coupled mechanism as design variables; the resonant frequency of the system, the distance between the coils, and the load size as constraints; and the transmission efficiency and transmission power as optimization objectives. Then the mathematical model is solved by the improved NSGA-II algorithm to obtain the Pareto optimal solution. Finally, the physical system is built to verify the correctness of the simulation experiment and the reliability of the experiment. This study is instructive for optimizing the transmission efficiency and output power of a magnetically coupled resonant wireless energy transmission system.