Quality function deployment （QFD） is a commonly used demand-driven solution design method and tool. To solve the fuzziness and uncertainty of evaluation information in QFD, spherical fuzzy was considered as it has the advantage of independently determining membership degree, non-membership degree and hesitation degree. Spherical fuzzy numbers were used to process expert semantic evaluation information, and the needs of suppliers and customers were mapped to engineering characteristics. To address the information loss problem due to inverse fuzzification in the existing fuzzy QFD analysis and the failure to consider the psychological preferences of decision makers, TODIM （Portuguese acronym for interactive multi-criteria decision-making） method was adopted to consider the psychological preferences of experts for risk avoidance and perform their importance analysis by calculating the overall dominance of engineering characteristics. In order to verify the effectiveness of the method, an electric vehicle product service system was used as an example to conduct the importance analysis of engineering characteristics, sensitivity analysis of loss avoidance coefficient, and to compare the results of ranking engineering characteristics of different multi-attribute decision methods. The results show that the proposed method can deal with the ambiguity and uncertainty of evaluation information, while taking into account of the risk preferences of decision makers, and is more consistent with the actual decision context.