Completed Clean Energy Engineering

On-street Residential Induction Charging

In plain English

AI plain-English summary

A lamppost-mounted charging pad will let residents in streets without driveways charge their electric cars by parking over a wireless induction plate, with no cables trailing across the pavement. The problem is straightforward: millions of people who park on the street cannot easily switch to electric vehicles because they have nowhere to plug in. Existing on-street chargers require cables across pavements, create trip hazards, and force residents to compete for a handful of bays. This project adapts wireless charging technology so it works with multiple vehicle makes, not just a single car model, and installs the ground pads in existing street furniture like lampposts. If the trial succeeds, the technology could remove the biggest practical barrier to electric vehicle adoption for terraced houses and flats. For local authorities, it means avoiding expensive trenching and new street furniture. For manufacturers, it opens a new customer base. For the UK supply chain, the project’s business models and service systems could become an exportable product, much as British engineering firms already sell transport infrastructure expertise abroad. The project runs in Redbridge, Milton Keynes, and Buckinghamshire towns.

View original technical description
The project's approach seeks to support business growth, to inform the creation of appropriate institutions to bring sectors together and to do this in a way that stimulates affordable green growth. Specifically, this project sets out to demonstrate an induction charging solution that provides a convenient on-street charging solution for residents who want to move to electric vehicles but need somewhere to charge while freeing up the streets from trailing cables and additional infrastructure, and alleviate the high contention for parking bays near the limited infrastructure. The project will unlock the wireless technology from specific vehicle and pad pairing, allowing for deployment to public streets and enabling its use by multiple vehicles. The project will provide benefits to transport practitioners by informing the design of business models and product service systems with a range of economic benefits: To the supply industry for wireless/wired systems for small vehicle services To EV manufacturers that would be able to reach users in residential areas that are currently unsuitable for EV adoption To service providers that can coordinate the joint delivery of infrastructure and retrofit kits and manage the complex back office tasks associated with energy provision, that could win export business in much the same way that UK management and engineering companies do for conventional transport development projects. Char.gy has a backpack charge point that attaches to lampposts and a satellite bollard charge point that utilise the power available in the lamppost giving the residents access to charging infrastructure outside their home without needing expensive additional infrastructure works. This project will take that solution and existing induction charging technology and modify it to be fitted aftermarket to electric vehicles across several vehicle manufacturers. The project will deploy the ground assemblies to residential streets in a London Borough - Redbridge, a regional city - Milton Keynes and towns in Buckinghamshire. WMG at the University of Warwick will be supplying parts of the induction charging and vehicle adaption solution. The Open University will identify and onboard local residents to the trial, engage with OEMs, facilitate the collection of data and disseminate the results of the project.

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Related Research

Grants with similar aims, by meaning.

Char.gy Residential Wireless Charging Feasiblity Study
Subsurface Technology for Electric Pathways (STEP)
Smart EV charging solutions for on-street applications
Expanding Urban E-mobility
Public residential street kerb charging system

Original classification

Collaborative R&D

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.