基于AI模型的跨学科防晕车评价体系研究

Interdisciplinary Study on Anti-motion-sickness Evaluation System Based on AI Model

由于电动汽车的加速性能和制动能量回收性能与燃油汽车不同,有些用户会产生不舒适的感觉,甚至晕车。文章研究防晕车功能缓解用户,尤其是乘坐者,对电动车的不适感,通过融合车辆参数、生理学和心理学建立提升舒适感的跨学科数据闭环AI模型,开发和优化防晕车功能。同时,模拟人脑思考的方式将AI模型和理论模型进行相互辅助,得出评价参数的关联度,建立防晕车的评价体系,经过试验测试,验证了评价参数与防晕车效果的一致性。通过评价体系迭代优化了防晕车功能效果,为电动汽车舒适性开发提供了开发方法论和评价体系。

Due to the different acceleration and regenerative braking performance of electric vehicles compared to fuel vehicles,some users experience discomfort,and even motion sickness.Mo⁃tion sickness prevention function has been studied to alleviate discomfort of users,especially passen⁃gers of electric vehicles.By integrating vehicle parameters,physiology,and psychology,an interdis⁃ciplinary data closed-loop model of comfort AI is established to develop and optimize the effect of antimotion sickness.Simultaneously,the simulation of human brain thinking mode is used to assist the AI model and theoretical model to obtain the correlation degree of evaluation parameters,and the evaluation system of anti-sickness is established.After experimental testing,the consistency between the evaluation parameters and the effect of anti-sickness is verified,and the effect of anti-sickness is optimized by the evaluation system iteration,which provides a development methodology and evalua⁃tion system for the development of electric vehicle comfort.