Optimal traction control for heavy-duty vehicles |
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| Affiliation: | 1. Department of Mechanical Engineering of Biosystems, Urmia University, Urmia, Iran;2. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;1. Department of Biosystems and Biomaterials Engineering and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea;2. SimLab Co., Ltd., Seoul, Republic of Korea;3. Unmanned Solutions Co., Ltd., Seoul, Republic of Korea;4. R&D Institute, Tongyang Moolsan Co., Ltd., Gongju, Republic of Korea;5. Environmental Materials & Components Center, Korea Institute of Industrial Technology, Jeonju, Republic of Korea |
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| Abstract: | Heavy-duty vehicles such as tractors, bulldozers, certain construction and municipal vehicles, soil millers, forestry machinery etc. have a high demand for propulsion force and consequently a high fuel consumption. The current work presents a traction control approach based on motion dynamics estimation for optimizing propulsion force and energy efficiency according to a user-defined strategy. Unscented Kalman filter augmented with a fuzzy-logic system for adaptive estimation is used as the state observer. Simulation case study with an electrically driven tractor is presented. The new method of traction control showed considerable improvement of balancing energy efficiency and propulsion force. |
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| Keywords: | Kalman filter Stochastic signal modeling Traction Optimization Simulation |
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