Special Issue on Virtual Sensing for Automotive Safety, Performance, and Predictive Maintenance Applications
The automotive industry has now reached an inflection point with radical changes coming across multiple dimensions. Technological advances are making modern vehicles more intelligent and interconnected. This increased intelligence often comes through accurate knowledge of the critical vehicle states, parameters, and inputs. Many of these variables are difficult to physically measure since the sensors required can be intrusive and/or expensive. Virtual sensor techniques offer an attractive alternative to direct physical sensors. They provide an economical and feasible alternative to impractical or costly physical measurements.
This Special Issue aims to cover the most recent advances in the usage of virtual sensing techniques in the context of automotive applications related to vehicle safety, performance, and predictive maintenance. The SAE International Journal of Passenger Vehicles and this special issue provide a peer-reviewed platform for both industry and academia to present new research and developments in this important area.
Topics of interest include, but are not limited to:
- Advanced signal processing algorithms and observer design for virtual sensors
- Machine/deep learning techniques for virtual sensors
- State-of-the-art review of virtual sensors, related challenges, and technical solutions
- Verification and validation tests for virtual sensors
- Functional safety considerations for virtual sensors
- Cost-benefit analysis of virtual sensors
- Virtual sensing for autonomous vehicles
- Virtual sensing for online fault and anomaly detection