Form generative approach for front face design of electric vehicle under female aesthetic preferences

Vehicles are the most representative product of both transportation and industry. Fueled by the growing popularity of energy-saving and environmentally friendly ideas and policies, new energy technologies and their supporting industries are experiencing constant development and refinement. As a result, electric vehicles (EVs) are steadily displacing traditional fuel-powered vehicles as the dominant force in the vehicle market. The experience economy is driving a significant shift in the direction of EV development, which is transitioning from improving functionality to optimizing the emotional connection consumers have with their vehicles. This means the form factor of the vehicle itself is becoming a key element in attracting consumers and influencing purchasing decisions. Over half of China's EV consumer market is comprised of females. However, many companies continue to develop products solely from a male perspective, missing out on a vast market opportunity. Therefore, incorporating design elements that cater to female aesthetic preferences into EVs can undoubtedly play a crucial role in unlocking this significant segment of the market. Based on this, the paper proposes a form generative design approach that specifically caters to the preferences of female consumers within the theoretical framework of Kansei engineering. The research process begins by obtaining Kansei imagery through the collection and analysis of big data. Subsequently, eye-tracking experiments are conducted to define the key design elements of the automobiles. Concurrently, appropriate aesthetic measurement indicator (AMI) system is established. Next, AMI values are computed for the sample set. This data is then leveraged to create a mapping relationship with the Kansei imagery, enabling the objective reflection of subjective aesthetic evaluations. Finally, an integrated Kansei evaluation equation serves as the fitness function within a generative approach that utilizes genetic algorithms and visual AI to produce form design solutions for electric vehicles. The evaluation confirms that the proposed design approach successfully generates a substantial number of high-quality creative solutions that align with female aesthetic preferences, while maintaining low cost and high efficiency.