Abstract: The Kansei evaluation of product form design reflects users’ perceptual cognition, of which the
characteristics of fuzziness and uncertainty render users hesitant and unable to precisely express their Kansei
preference. To address this problem, the hesitant fuzzy linguistic term sets (HFLTSs) were introduced to describe
users’ Kansei evaluation. With the mathematical operators of HFLTSs, a consensus model was constructed to measure
the consistency degree of users’ perceptual cognition about product form design schemes. The particle swarm
optimization technique (PSO) was utilized to optimize users’ Kansei evaluation matrices for consensus reaching. With
optimized Kansei evaluation matrices, the technique for order preference by similarity to an ideal solution (TOPSIS)
was applied to rank product form design schemes. A Kansei evaluation process of product form design based on
HFLTSs and PSO was proposed. The Kansei evaluation of car charging pile design schemes as an example verified
that HFLTSs can be conducive to solving the uncertainty and hesitancy problems of users’ perceptual cognition, and
that by integrating PSO for consensus reaching, the consistency of Kansei evaluation with HFLTSs can be improved, and finally the quality of Kansei evaluation of product forms can be enhanced.

Key words: product form design, Kansei evaluation, hesitant fuzzy linguistic term sets, particle swarm optimization;
consensus reaching