Sentience - The Development of Location-Aware Vehicle Control Strategies
Andrew Preece, Ricardo
This session presents the Sentience project, which has pursued the application of information about a vehicle’s future route to improve fuel consumption. The project, a collaboration between Ricardo, Orange, TRL, Jaguar Land Rover, Ordnance Survey, and Innovits, has shown significant fuel consumption improvements on a demonstration hybrid vehicle.
During the initial phase, concepts were developed on the desktop using MATLAB and Simulink. Dynamic programming was used in MATLAB to provide a basis for strategies, which were developed in Simulink making use of a detailed vehicle model. Use of Real-Time Workshop coupled with the extensive use of the Embedded MATLAB® subset within the model allowed the rapid development of complex algorithms to the vehicle in the subsequent phase.
Three distinct fuel-saving strategies were developed:
- Enhanced acceleration/deceleration provides an advanced cruise control that matches the vehicle speed to the road ahead, avoiding fuel-wasting harsh braking and acceleration. This strategy is applicable to any vehicle.
- Intelligent air conditioning reduces the need to run the engine wastefully when the vehicle is stationary by anticipating stops and precooling the vehicle. This strategy is most applicable to mild hybrids and vehicles implementing stop/start.
- Optimized engine load manages the split of power between the engine and motors of a hybrid vehicle so that battery charging takes place at the optimum points along the route.
The demonstration vehicle was subjected to an extensive test program: on the road, on a test track, and in a climatic chamber. MATLAB was used to process the test results and derive calibration improvements.
Results showed an estimated 10% CO2 and fuel saving in real-world U.K. driving.
Recorded: 22 Jun 2010
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