2021 marked a watershed moment for electric vehicles (EVs) in the UK, seeing a 76.3 per cent rise in sales. People bought more electric cars this year than in the previous five combined.
EVs are expected to represent 91 per cent of all new car sales by 2030, as the government enacts a ban on the sale of new petrol, diesel, and hybrid vehicles. EVs are therefore key to meeting our net zero commitments by 2050. And yet, there remain significant barriers to the mass-market adoption of EVs – from concerns over charging infrastructure to preparations for heightened electricity demand.
Accelerating an equitable transition
Investors are giving ever more weight to sustainability, and legislators are debating charges on carbon emissions, inspiring logistics providers and car services companies to invest in fleet electrification.
However, concerns over the provision of charge points remain one of the biggest barriers to companies electrifying their fleets and people buying EVs, particularly in 'left-behind' areas. In much of the North West, there are less than 23 charge points per 100,000 people, compared to the capital's 87, meaning there are not enough to make the purchase of an EV viable for many private individuals and fleet operators.
While this remains the case, encouraging people and businesses to adopt EVs risks further alienating communities that lack access to ample charging technology. This could result in individuals and SMEs needing to dedicate extra time and/or resources to route planning and logistics – adding greater economic and time costs to an already squeezed society. Left unchecked, this inequitable access risks curtailing the mobility of those who cannot easily access the charging network.
We cannot allow the transition to net zero to create a new social divide.
Predictive analytics with machine learning capabilities is addressing this challenge by accelerating the equitable rollout of street charging infrastructure. Its adaptive models identify gaps in current provision and leverage anonymised mobility patterns and demographic data to forecast future demand. These models empower planners, developers, and local authorities to better target investment in deprived areas and develop holistic plans for the rollout of EV charging infrastructure, driving new demand.
Such innovations are helping address concerns over the provision of charge points while supporting the government's 'levelling up' agenda, with companies financing the construction of electric car battery plants in 'left behind' areas such as Blythe. They will play an increasingly important role in an equitable transition to net zero, ensuring that
those within less affluent areas have the same opportunities as those in more affluent locales.
Keeping EVs on the road
The rollout of EVs and charging infrastructure will pose serious challenges to the UK's six Distribution Network Operators (DNOs), requiring them to reinforce their networks and regularly monitor fluctuations in pressure on the grid. Failing to address these challenges could leave them unable to meet expectations and regulatory targets, meaning people may reach charge points only to find them 'empty'.
One electricity DNO is already using predictive analytics to prepare for heightened demand, leveraging multiple data sets to estimate where and when they are likely to see peaks and troughs in electricity usage. The machine learning models developed from this data have become adept at providing full visibility of their networks' demand profiles, bolstering capacity.
By embracing such innovations, DNOs can ensure that they are ready to meet heightened electricity demands, keeping EVs on the road.
Data-driven standards
The government's decision to phase out fossil fuel-powered vehicles presents the UK with an opportunity to set the standard for delivering a successful rollout of EV infrastructure. We need to act decisively based on the insights provided by predictive analytics and data-driven modelling to ensure that our transition to sustainable transport is both smooth and equitable.
Read CKDelta's latest report, Predictive Analytics. Powering an Electric Vehicle Revolution here.
Geoff McGrath is an entrepreneur, strategist, innovator and technologist. For over eight years, Geoff was the former chief innovation officer for McLaren Applied, where he took insights from the world of Formula 1 to drive change in the wider transport sector and beyon. Geoff is now the Managing Director of data science business, CKDelta. To find out more, please visit: www.ckdelta.ie
