The progress of the project beyond the state of the art include the following findings: 1) the size of the components, especially the heat exchanger plays an important role in dynamic modelling and control of the ORC system. For highly transient heat sources, the dynamic modelling and control aspects should be incorporated in the preliminary design; 2) the non-linear model predictive controller outperforms the conventional proportional–integral–derivative controller; 3) implementation of an optimized non-linear model predictive control based ORC system for long haul truck can reduce the fuel consumption by 14%.
Development of the dynamic model and optimize controller will lead to improvements in overall system efficiency of the ORC system for waste heat recovery from internal combustion of heavy duty vehicles, and increase the uptake of low carbon technologies in transportation sector. This will lead to reductions in CO2 emissions, resulting in a positive impact on the climate whilst reducing the fuel consumption. In broader terms, the project will contribute to the development of a more efficient energy system for vehicles, reducing the fuel consumption and carbon dioxide emissions of the transportation sector, thus helping to attain socio-economic and environmental targets. The successful commercialization of the ORC system for waste heat recovery from internal combustion of heavy duty vehicles will furthermore create new business and job opportunities.
The development of safe and efficient controller will lead to improvements in overall system efficiency of the ORC system. This will lead to reductions in CO2 emissions from transportation sector. Furthermore, developing expert knowledge in this field will lead the way for future commercialisation, stimulating investment and creating new jobs and businesses within the energy sector.
