To preserve the fun of driving and enhance driving convenience, a smart regenerative braking system (SRS) is developed. The SRS provides automatic regeneration that is appropriate for the driving conditions, but the existing technology has a low level of acceptability and comfort. To solve this problem, this paper presents an automatic regenerative control system based on a deceleration model that reflects the driver&rsquo

s characteristics. The deceleration model is designed as a parametric model that mimics the driver&rsquo

s behavior. In addition, it consists of parameters that represent the driver&rsquo

s characteristics. These parameters are updated online by a learning algorithm. The validation results of the vehicle testing show that the vehicle maintained a safe distance from the leading car while simulating a driver&rsquo

s behavior. Of all the deceleration that occurred during the testing, 92% was conducted by the automatic regeneration system. In addition, the results of the online learning algorithm are different based on the driver&rsquo

s deceleration pattern. The presented automatic regenerative control system can be safely used in diverse car-following situations. Moreover, the system&rsquo

s acceptability is improved by updating the driver characteristics. In the future, the algorithm will be extended for use in more diverse deceleration situations by using intelligent transportation system information.

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The different versions of the original document can be found in:

https://doaj.org/toc/2032-6653 under the license cc-by
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Published on 01/01/2019

Volume 2019, 2019
DOI: 10.3390/wevj10040058
Licence: Other

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