Big data to make construction more fuel efficient Tuesday, 29 November 2016

Warwick Manufacturing Group (WMG), an academic department at the University of Warwick in the UK, has developed an intelligent software that will make construction vehicles more fuel efficient and environmentally-friendly. 

Many off-highway vehicles are left running at full power whilst idle for much of their life. These vehicles, including telescopic handlers, heavy excavators and wheeled loaders, potentially waste fuel, while directly impacting local air quality with emissions. 

WMG is working with partners JCB and Pektron to optimise the fuel economy of the next generation of off-highway vehicles, by introducing new intelligent power systems that lead to improved engine operation.  

According to Dr James Marco from WMG, this work could lead to significant fuel savings and fewer carbon emissions for the industry. 

Marco’s team is analysing JCB’s current fleet to reach a better understanding of the opportunities for emissions reduction and intelligent control. 

Today’s construction industry is more environmentally-conscious than ever. The amount of carbon dioxide emitted released by vehicles can affect the players chosen for a particular project or contract. 

With an increasingly demanding marketplace, construction vehicle fleets that have lower emissions and better green credentials are seen as being much more competitive. 

WMG is analysing the suitability for micro/mild hybridisation (MMH), a low-cost and simple implementation to improve fuel efficiency. 

The intelligent use of MMH could provide the opportunity to shut down the engine, or shift it to lower power, during idle periods. This would have a measurable impact upon reducing fuel consumption, CO2 output, NOx formation and particulate emissions. 

Another component of the WMG research is technology that predicts when machinery needs to shift between low and high power. Users can thus run their vehicles with the lowest fuel consumption without sacrificing their working performance. 

Behind this technology is an advanced methodology for big data capturing, compression and mining from the telematics of the construction equipment fleets, allowing easy management and analysis of the performance of various machine types. 

WMG’s tool will enable companies to target specific machines among their fleets for hybridisation.