###### Abstract
(2021) proposed an integrated multi-field optimal design with a collaborative optimization and approximation technique to improve ride comfort, reducing the fluctuating range of the front wheel and improving the steering experience, using a mathematical model of a 7-degrees of freedom electric power steering (EPS) system and a simulation model of the front wheel suspension ([PERSON] et al., 2020). However, since it is not a model capable of predicting ride comfort and steering performance, which are actually developed on an emotional basis, it is difficult to optimize to achieve the goal required during vehicle development. As can be seen from the results of previous research, vehicle manufacturers do not rely solely on simulation to establish a chassis platform design goal to satisfy ride and handling performances. For this reason, most vehicle manufacturers perform ride and handling performance tests by manufacturing test vehicles with chassis parts designed using various methods. In order to improve the performance lacking in the test results, a test vehicle is manufactured with redesigned chassis parts, and a ride and handling performance test is performed. Vehicle manufacturers repeat these processes (design, manufacture, and test) at least three times in order to achieve the performance target of a vehicle to which a new chassis is applied. As the number of repetitions of this process increases, the cost of manufacturing a test vehicle and the number of work hours required for development increase, but a test vehicle is a prototype made in small quantities. As for the manufacturing cost, the first test vehicle costs more than about $300,000, the second test vehicle costs more than about $200,000, and the third test vehicle costs more than about $100,000. However, since it is necessary to manufacture a test car for each trim and sales region, it generally costs several million dollars. Therefore, many manufacturers, including Hyundai Motor Company, are trying to introduce a virtual development process to minimize the number of iterations of the development process dependent on the real object. The tasks to be solved to increase the accuracy of setting design goals using virtual models are summarized as follows. With a simulation model that predicts quantitative values, it is difficult to predict ride and handling performances, which are emotional evaluation items. * Insufficient analysis of the predictive consistency of the simulation model for quantitative measurement items related to ride and handling performance. * Lack of consideration for direct application to actual design. In this study, to efficiently achieve the handling performance goal of Hyundai Avante N, a high-performance vehicle, the following steps were followed for setting the K&C characteristics of the chassis corresponding to the design target before the design process. * Establish a quantitative measurement item that matches the handling rating, which is an emotional evaluation item, and develop a relationship between them. * Build a virtual model with predictive consistency for quantitative measurement items related to handling performance. * Optimize the chassis characteristics to achieve the vehicle performance goal: Optimize step-by-step using a factor sequence with a smaller impact on other fields. * The cause of performance improvement is analyzed when applying the design factors obtained by optimization to clarify the direction of improvement. * Provide priority information that needs to be applied through analysis of the performance impact by a factor that changes as a result of optimization.