Optimization designation of automobile rotating distribution disk reducer based on the improved dung beetle optimizer algorithm
To address the problem of large size and low transmission efficiency in the automobile rotary distributor reducer,an improved dung beetle algorithm(IDBO)was used to optimize the design.Firstly,a Circle chaos mapping was introduced to initiate the population sequence so as to make the initialized dung beetle population distribution more uniform.Secondly,a multi-directional learning strategy was applied to update the individual positions of the ball-rolling dung beetles in the no-obstacle mode in order to jump out from local optimal solutions and enlarge the searching range.At the same time,adaptive t-distribution variation perturbation was used to update the positions of dung beetles so as to improve the algorithm's global and local search ability,and to make it converge quickly.Finally,to minimize the total volume and transmission power loss,the IDBO was utilized to optimize the design of the gearbox.The results show that the optimized reducer can reduce the volume by 44% and the transmission power loss by 28% .Compared with other intelligent optimization algorithms,the optimization result of IDBO is better.
worm helical gear two-stage reducerimproved dung beetle optimizer(IDBO)algorithmtotal volume of spacetransmission power loss
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