Development of a six-wheel drive vehicle: A comparative study on steering performance
The innovation for the recent agriculture tractors have been widely developed. These tractors are used to enhance the harvesting activities in way to lowering the labour cost. However, the current system of infield collection of oil palm fresh fruit bunches by using mini-tractor-trailer (MTT) has its limitation. This MTT have poor traction on soft ground such as coastal and peat areas which give the limiting factors that prohibit the usage of any mini-tractor. Thus, the aim of this project is to fabricate a functioning prototype vehicle consist of two-wheel steering (2WS) and four-wheel steering (4WS) in measuring its performance of tractive effort and steering radius for usage in palm plantation. The machine configuration consists of main chassis, compartment to carry oil palm bunches, a mechanism for loading purposes, operator cabin, and associated hydraulic system. The labouratory test of performance evaluation were conducted to the developed vehicle. The results show that under four-wheel drive (4WD) mode, the turning radius of the vehicle was found to be 42.9% lesser if the 4WS mode is engaged. For 6WD with 4WS active, the turning radius was 46% lesser while turning for 42.2% lesser compared to 2WS. The slippage ranges are recorded between 8.5% to 22.5% where the slippage for the left wheel is negative as the left wheel rotates slower than the right wheel on the left turning of circular motion and vice versa. In addition, the vehicle design could be considered optimum as the measured tractive effort of the vehicle was found to be 32% of the vehicle gross weight. This is within the recommended tractive effort, which is within
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2019 Abd Rahim Shuib, Mohd Azwan Mohd Bakri, Mohd Khairul Fadzly Md Radzi
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.