Project Summary
The project aims to create a cost-effective and efficient method for evaluating the efficacy of technological interventions in decarbonising Heavy Goods Vehicles. Utilising a novel data-driven approach, they aim to eliminate the need for lengthy and expensive in-service trials that are subject to external factors. Their method will be validated through a combination of laboratory wind tunnel tests, controlled track tests, and normal operations. This approach will allow fleet operators to quickly evaluate the effectiveness of interventions and make informed decisions regarding decarbonisation.
Project Achievements
The data-driven assessment approach developed and validated from this project takes advantage of the high-resolution HGV operations data provided by the vehicle Fleet Management System (FMS) interface, and features mining for dynamically comparable driving conditions from real-world HGV operations while excluding the influence of various operational factors that have been confounding conventional analysis. In this project, the fuel-saving benefit of an optimised cab deflector design was quantified by using the proposed data-driven approach to the high-resolution data collected from the two HGVs during their real-world operations over a period of 3 months. One of the two HGVs were fitted with the optimised cab deflector of interest whilst the other with a default (baseline) cab deflector. These two HGVs were also experimented in a controlled environment on a test track. Results derived from the controlled experimental measurement were found agreeing very well to those obtained from the real-world analysis using the proposed data-driven approach.
Conclusions
A 3.8 to 6.6% fuel-saving benefit of the optimised cab deflector, compared to the baseline deflector was identified in the motorway driving condition under a vehicle weight of 32 t, through applying the proposed data-driven assessment approach to the high-resolution in-service data. The controlled experiment results showed that the HGV with the optimised cab deflector enjoys a reduction of aerodynamic drag by 11.69%, which suggests a 5.6% fuel saving for an HGV of the same weight and in the same motorway driving condition. The fuel-saving results obtained from the two independent analysis matched very well.
Next Steps
Two tasks are expected to be carried out in the next stage. The first involves extensively validating the data-driven approach developed from this project across a variety of HGV decarbonisation interventions. The second involves establishing a university spin-out focusing on exploiting the data-driven approach and selling a minimum viable (MVP) software toolkit that supports HGV fleet operators’ decarbonisation initiatives through proving timely, accurate and reliable assessment of carbon saving analysis.
