AES 5th International Conference on Automotive Audio

This paper explores the use of virtual sensing in a feedforward active noise cancellation (ANC) system for an electric vehicle. Vibration reference signals and microphone disturbance signals were recorded in an electric vehicle operating in cruise control mode at various driving speeds. The dataset was used to test the Remote Microphone (RM) and Auxiliary Filter (AF) virtual sensing methods and to investigate their sensitivity to variations in road speed and acoustic conditions. 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. The optimisation methods and control algorithms developed here could be readily used on other datasets to further investigate the use of virtual sensing.

Haptic technologies are being increasingly employed as part of automotive sound reproduction systems to enhance listener immersion within the rendered soundfield. Recent research on the use of audio haptic transducers as a means of providing a multi-sensory experience of sound has focused on characterising the performance of transduction devices. To date, performance evaluation has been restricted to experimental conditions in which haptic transducers have been measured individually with specific unit mounting and load conditions. This research demonstrates the validity of extending existing performance evaluation methods and metrics to in situ systems (e.g. those employed in an automotive setting). Specifically, a system of four individual haptic transducers mounted on the backrest of an automotive seat is evaluated, with and without system tuning strategies applied, using accelerometer measurements. Results demonstrate that system response characteristics can be tuned via frequency equalization and input signal dynamics pre-processing with the tuning quantified through use of existing performance metrics. In particular, it is shown that the overall response of the system under test may be optimised through analysis and tuning of each separate transducer individually.