DfT survey reveals views on electric vehicles and charging

People’s perceptions of electric vehicles (EVs) and charging on the public network have been revealed in new Government research.

It found drivers were split over the demand on infrastructure, with more than a quarter (27%) saying that ‘most’ public charge points have ‘long queues’ – up from 18% in 2022.

However, the Department for Transport (DfT) figures, from the latest National Travel Attitudes Study, had a similar proportion of respondents (26%) claiming the complete opposite.

Interestingly, 31% of those aged between 16 and 39 years agreed that there are long queues for public charge points, compared to 19% of those aged between 60 and 69 years.

Last July, when the RAC predicted one of the busiest days ever for EV charging, Moto announced it was deploying marshalls to manage increased demand at charge points.

The reality is the vast majority of EV drivers currently charge their vehicles overnight at home and, if they do charge on the public network, long queues are few and far between.

Nevertheless, a negative perception does not appear to have a significant impact on the buying intentions of motorists.

Of those respondents to the DfT survey who agreed that public charge points have long queues, almost half (46%) say they are likely to make their next car purchase an ultra-low emission vehicle (ULEV).

Conversely, those who disagreed that there are long queues, just over half (55%) say they are likely to make their next car purchase a ULEV.

The DfT survey also revealed that 45% of respondents had low to no knowledge of EVs, compared to 37% who rated their knowledge as high.

Males were more likely to rate their own knowledge highly (47%, compared to 28% of females), and conversely females were more likely to rate their knowledge towards the low end of the scale (56%, compared to 32% of males).

Matas Buzelis, car expert at vehicle history checking service CarVertical, said: "Take-up of electric cars looks set to accelerate rapidly if the Department for Transport’s findings that half of drivers planning to buy a new car will opt for an ultra-low emission vehicle prove to be true.

“What might hold sales back is the finding that 45% of survey respondents had low to no knowledge of electric cars.

“There is much still to be done to encourage drivers to choose greener cars, especially if many do not understand the benefits. The lack of charging points also remains a huge barrier to the take-up of plug-in cars.”

A recent study conducted by Field Dynamics concluded that Great Britain is anticipated to need eight times more public EV chargers to meet the growing demand by 2035.

Through analysis of 140 million MOT records and EV efficiency, the net zero data consultancy claims to have gained precise insights into vehicle energy demand.

The Field Dynamics research assumes a third of the car and van fleet would have transitioned to electric power by 2035.

A third of the on-street energy demand of Great Britain is 7.3 TWh. Comparatively, the capacity of the public EV charger network is 0.9 TWh, based on a 15% utilisation rate, revealing a substantial gap of 6.4 TWh.

Meeting the modelled demand would require just over an eight-fold increase in energy, which Field Dynamics says could equate to 120,917 slow chargers, 46,150 rapid chargers, 39,926 ultra-rapid chargers and 234,700 fast chargers.

However, it says that this does not factor in charger efficiency, improved utilisation rates, human behaviour and the integration of faster chargers.

Currently, there are 50,000-plus chargers on the public network and Government has set a target of delivering 300,000 chargers by 2030. 

Craig Stephenson, director of Field Dynamics, said: "Historically, answering the question of how many chargers we need has been an exercise in speculation based on opinions.

“Now, after analysing 140 million MOT records and factoring in EV vehicle efficiency, GigaMap can provide actual kilowatt-hour (kWh) power demand figures for both public and private charging down to LSOA level based on real-world data.”