浙江大学学报(工学版)  2018, Vol. 52 Issue (9): 1658-1666    DOI: 10.3785/j.issn.1008-973X.2018.09.005
 土木与水利工程

Non-isometric crossover evolution algorithm of Markov chain for designing vehicle driving cycles
ZHANG Man, SHI Shu-ming
College of Transportation, Jilin University, Changchun 130022, China
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Abstract:

A non-isometric crossover evolution algorithm for designing vehicle driving cycles with Markov property was proposed, in order to solve the low efficiency and poor quality caused by the Markov Chain and typical genetic algorithm when designing vehicle driving cycles. Individuals were designed to satisfy the Markov property by exchanging with non-isometric cross segments; a new crossover was designed based on the genetic algorithm, which broke the restriction of allelic crossover segments and was applicable for designing driving cycles. According to a collected highway database, the method was used to design three-parameter highway driving cycles, which included constructing non-isometric initial populations and designing an objective function by using the satisfaction rule model and exponential weighted average. Three kinds of three-parameter representative driving cycles with different lengths were generated. Results show that the relative deviations of indices between the desired cycles and the original database are within a reasonable range and correlation coefficients of velocity and acceleration joint probability distribution are above 90%, which indicates the representativeness of the generated driving cycles. Compared with the results of the method which combines Markov Chain with typical genetic algorithm, the average design efficiency of the new method increases by 66%, and the design quality of driving cycles is better.

 CLC: U467

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ZHANG Man, SHI Shu-ming. Non-isometric crossover evolution algorithm of Markov chain for designing vehicle driving cycles. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(9): 1658-1666.

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