Abstract
To increase productivity and efficiency, modern agriculture is becoming more and more dependent on technology. This paper investigates the creation and use of Electronic Differential Systems (EDS) to improve the efficiency of agricultural equipment. The application of EDS to the agricultural industry has great potential. EDS is a technology that is frequently used in automotive engineering to optimize traction and stability. Using EDS in agriculture has several advantages. Even in difficult field conditions, it enables precise control of the power distribution to the wheels, reducing wheel slip, and improving traction. It increases the maneuverability of agricultural machinery by maximizing power distribution during turns, minimizing soil compaction and crop damage. EDS also helps with fuel and energy efficiency because it enables intelligent power delivery management, which reduces energy waste and increases the operational range of agricultural vehicles. This effectiveness is crucial for environmentally friendly farming practices and sustainable agriculture. In our review, simulation many previous researches take into consideration to performs in a variety of agricultural scenarios, such as field work, planting, and harvesting operations. We seek to optimize the EDS control strategy's performance in agriculture by analyzing the simulation results. Precision farming has advanced greatly with the use of Electronic Differential Systems (EDS) in agricultural equipment. This research demonstrates how EDS has the potential to boost energy efficiency, increase maneuverability, decrease soil compaction, and improve traction in the agricultural industry. The findings support efforts to update farming methods and guarantee the sustainable production of food.
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El Mourabit, A., Hadj Baraka, I., Can, İ., Bergor Beguiel, B. (2024). Development and Application of Electronic Differential Systems (EDS) for Enhanced Agricultural Machinery Performance. In: Ezziyyani, M., Kacprzyk, J., Balas, V.E. (eds) International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD'2023). AI2SD 2023. Lecture Notes in Networks and Systems, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-031-54318-0_9
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