Application of virtual sensing strategies for active control of road noise in an electric vehicle

Wilmshurst L, Elliott S, Vered Y, Shi C. Application of virtual sensing strategies for active control of road noise in an electric vehicle. In: AES 2024 International Conference on Automotive Audio. Audio Engineering Society; 2024. Paper 4. Available from: https://aes.org/publications/elibrary-page/?id=22613

@inproceedings{Wilmshurst2024_22613,
  author = {Wilmshurst, Laurence and Elliott, Stephen and Vered, Yoav and Shi, Chuang},
  title = {{Application of virtual sensing strategies for active control of road noise in an electric vehicle}},
  booktitle = {AES 2024 International Conference on Automotive Audio},
  note = {Paper 4},
  year = {2024},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22613}
}

TY  - CPAPER
TI  - Application of virtual sensing strategies for active control of road noise in an electric vehicle
AU  - Wilmshurst, Laurence
AU  - Elliott, Stephen
AU  - Vered, Yoav
AU  - Shi, Chuang
T2  - AES 2024 International Conference on Automotive Audio
M1  - Paper 4
PY  - 2024
DA  - 2024/06/17
UR  - https://aes.org/publications/elibrary-page/?id=22613
PB  - Audio Engineering Society
LA  - en
AB  - This paper explores the use of virtual sensing in a feedforward active noise cancellation (ANC) system for an electric vehicle. The aim is to test and compare the Remote Microphone (RM) and Auxiliary Filter (AF) virtual sensing methods by applying them to a dataset of vibration reference signals and microphone disturbance signals, which were recorded in an electric vehicle operating in cruise control mode at two driving speeds. The necessary observation/auxiliary filter matrices were estimated in an initial identification step and the optimal Wiener control filters were then separately calculated for each scenario. The standard RM method gave slightly better results than the AF method and was less computationally expensive. This was improved upon using a variant of the standard RM that minimises a delayed version of the error signals. The optimisation methods and control algorithms developed here could be readily used on other datasets to further investigate the use of virtual sensing.
ER  -