As road surfaces deteriorate, they grow rougher, and that roughness makes a vehicle work harder to keep moving. For electric vehicles, where every unit of energy is drawn from a finite battery charge, a rougher road is in effect a hidden tax on range. But how much energy does an electric vehicle lose simply because the road beneath it is rough?
The FTVG-supported project “The Hidden Energy Tax: Quantifying the Road Surface Roughness Penalty for EV Battery Range on UK Urban Roads” is investigating how pavement surface condition affects the energy consumption of Battery Electric Vehicles (BEVs) under real-world UK driving conditions.
The study is led by Dr Nadia Naqvi, Lecturer at Anglia Ruskin University Peterborough, with Dr Izza Anwer, Assistant Professor at the University of Engineering and Technology Lahore, as collaborator. Together they bring road-condition measurement, vehicle telemetry and statistical analysis to bear on an issue that sits at the intersection of highway asset management and the transition to electric mobility.
The pilot study is designed to produce a UK-specific empirical estimate of the relationship between road roughness and BEV energy consumption, evidence that could help highway authorities consider vehicle energy costs alongside more conventional factors when making road maintenance and infrastructure investment decisions.
“The value of this work is that it connects two questions usually kept separate, ‘how we maintain our roads, and how efficiently electric vehicles use energy’ and shows they are really one question,” says Nadia.
As pavements deteriorate, their surfaces become rougher. Poorer surface condition can increase the forces acting between a vehicle and the road, and consequently increase the energy required to travel along it. For internal combustion engine (ICE) vehicles, previous research has established a relationship between pavement roughness and increased fuel consumption and vehicle operating costs. Evidence relating road roughness specifically to EV energy consumption, however, remains much more limited, particularly under UK road conditions.
That gap is increasingly important as BEVs become a larger part of the vehicle fleet. For an EV, additional energy consumption does not simply represent an operating cost: it can also reduce the distance available from a battery charge. Understanding whether deteriorated roads impose a measurable energy penalty could therefore add another dimension to the economic case for timely road maintenance.
The project asks a practical question, how much does road surface roughness change BEV energy consumption under real-world UK conditions?
Rather than relying solely on simulation or laboratory estimates, the project uses a field-based experimental design on roads in Peterborough. Four pairs of road segments are planned for the study. Within each pair, the roads will be matched as closely as possible for characteristics such as road classification, speed limit, intersections and gradient, while differing in pavement condition.
Road condition will be characterised using the International Roughness Index (IRI), with smartphone accelerometer-based measurements used alongside available SCANNER road-condition data from Peterborough City Council. An electric vehicle will travel across each selected segment under controlled conditions, with energy consumption captured through vehicle telemetry. Environmental conditions including temperature, wind speed and wind direction will also be recorded, while road gradient and vehicle speed will be incorporated into the analysis. Separating the effect of pavement roughness from these competing influences is central to the study, and a multiple linear regression framework will be used to estimate the relationship between IRI and BEV energy consumption while controlling for relevant operational and environmental factors.
“Measurement rigour and real-world validity is treated as core tests from the outset — the method has to be defensible before the results can mean anything,” says Izza.
The project is not concerned only with producing a single numerical result. A second objective is to develop and test a replicable field methodology combining pavement condition measurement with vehicle telemetry, an approach that could subsequently be applied to other road networks and vehicle types. That matters for moving from a focused feasibility study toward large-scale research capable of examining how the relationship changes across different vehicles, roads and operating environments. The study therefore tests both a hypothesis and a measurement framework.
The project has already moved from concept into active data collection and stakeholder engagement. Road condition data (RCI) for the network has been acquired from Peterborough City Council. Using QGIS, this data has been mapped across the city to highlight the condition of individual road sections, distinguishing good from poor and giving a clear spatial picture of where the network is deteriorating and where recent maintenance has been effective.
Alongside the data work, stakeholder meetings have been arranged to discuss the research and explore opportunities for collaboration. These conversations have been positive and have opened pathways to extend the study, particularly toward rural road sections, which remain among the least funded and least monitored parts of the network and where a low-cost measurement method could add the most value.
Several corridors have now been selected and the survey is under planning. Test runs have already been carried out on some of these to record preliminary data, and these early runs are being used to refine the measurement protocol and confirm the data collection workflow ahead of the main survey campaign. New SCANNER survey data is expected in early autumn, allowing the team to examine roads that have recently received maintenance intervention.
The project is expected to produce three principal outputs. First, a UK-specific empirical estimate linking pavement roughness to BEV energy consumption. Second, a field-based methodology that could be replicated across other UK regions and vehicle types. Third, the findings will be communicated through a comprehensive project report and engagement with highway and professional stakeholders, helping translate the technical results into evidence relevant to infrastructure investment and maintenance decisions.
The wider implication is that the condition of a road may have consequences beyond ride quality and conventional vehicle operating costs. If deteriorating surfaces measurably increase EV electricity consumption, maintaining smoother roads could contribute to transport system efficiency as the vehicle fleet becomes increasingly electrified.