Kansei engineering is a Japanese approach by which products and services are developed and improved with consumers' psychological feelings and needs incorporated into the design domain. This paper proposes a new Kansei evaluation method in which human perception properties in vehicle steering wheel operation are considered. The method does not involve consideration of steering wheel machine characteristics in their pure form; rather, psychological feelings and needs (Kansei) are evaluated using statistical techniques after these characteristics have been converted for representation in a human subjective force perception space. In this way, the relationship between Kansei evaluation results obtained using a semantic differential method and the machine characteristics of a steering wheel can be modeled. Kansei items can also be optimally designed using mathematical programming. In this study, an algorithm for the proposed method was formulated and a Kansei evaluation experiment was conducted. The results clearly showed that modeling accuracy for all Kansei items is improved by the conversion of machine characteristics for representation in a human subjective force perception space as compared to a case in which machine characteristics were used without conversion. The outcomes (1) confirmed the validity of converting machine characteristics for representation in a human subjective force perception space, and (2) proved that optimal design using estimated models of Kansei evaluation allows the derivation of machine characteristics suitable for a targeted Kansei item.