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Why more data can mean less carbon for delivery networks

(Image credit: Image Credit: Flickr / janneke staaks)

When talking about the future of mobility, the auto industry talks a lot about CASE – that is, connected, autonomous, shared, and electric vehicles – as the right response to the increasingly urgent need to decarbonise our transport networks.

We have recently seen significant movement on the electric aspect of this. In the UK, for instance, the government is bringing the ban on the sale of conventional vehicles forward to 2035 and potentially to 2032 (1), while a recent survey we conducted showed that 89 per cent of companies expect EVs to play a dominant role in their fleets by 2028 (2). It’s clear that this shift will help us to reduce the carbon emissions generated on our roads.

For shared and autonomous transport, too, it’s easy to see how having fewer vehicles moving more efficiently will lighten the burden we place on the environment when moving people and goods around. The connected aspect of this equation contributes to carbon reduction, however, is perhaps less clear. Shared and autonomous vehicles will probably also need to be connected vehicles, yes, but can connectivity bring something to the table itself as well as making other initiatives possible?

Understanding vehicles as data

Just as we have recently seen the automotive industry throw its weight behind an electrified future, producing more models in the last few years than we have seen in decades previously, IT has for some time been realising the power of big connectivity and big data.

By bringing together large datasets and designing tools – often automated – to efficiently understand them, companies in every sector have been transforming their processes and doing more, and better, with less. Now, emerging commercial fleets of electric vehicles have the opportunity to use the same principles in order to offer a decarbonised alternative to firmly established, cost optimised companies operating vehicles with internal combustion engines (ICE).

Gnewt (3) , for example, is a last-mile delivery company which today operates one of the largest electric fleets in the UK During the company’s growth, however, it had a significant challenge as its depot could fully charge just 35 vehicles per day, putting a seemingly hard cap on its fleet size. Facing competitors which are both incumbent players and – as they use internal combustion engine (ICE) vehicles – don’t experience the operational constraint of long charging times, Gnewt needed to increase capacity while keeping its expenditure in line with revenue.

The problem turned out to be not just the number of charging points or overall power supply which was available, but the lack of insight into how vehicles are charging. The company’s fleet is composed of vehicles from multiple automakers, and while all have intelligent data reporting systems pre-installed, these competing and incompatible systems made overseeing the whole fleet at once impracticable. The solution was a third-party data platform which bundles all of that data into a single API, such that all of the company’s vehicles could feed into a central point of management.

This shift, basic though it seems, by itself increased the number of vehicles which can be charged per day to 80 – simply by making sure that no charge time goes to waste.

From efficiency, to insight, to revenue

There is a rich wealth of data which vehicles generate, and which can interact with the world around them to create new ways of operating. A key example of this is a vehicle battery’s health. While electric vehicles ultimately have lower complexity and fewer moving parts than their traditional counterparts, much of the cost of a vehicle, not to mention its usefulness, is tied up in the enormous batteries required to power it.

Unlike a fossil fuel engine, however, batteries are natively able to report on their status digitally – and pulling together and analysing that data can be enormously valuable. For the individual company, that means always knowing that a vehicle will have the capacity to complete its day’s work, and knowing exactly when to replace a vehicle for maximum return on investment.

Across the huge number of electric vehicles now on our roads, that means that we can start to map precisely how different vehicles perform over time (4), and how factors such as charging voltage, local climate, and usage patterns affect battery health. This is real-world data of a scale and depth that just can’t be replicated in the lab.

This, of course, goes alongside telematics data such as speed, location, dwell time, and many other data points which when analysed together can deliver surprising results for fleet owners. Always-on awareness of a vehicle’s charge state, for instance, also means that charge which is ‘left over’ at the end of a vehicle’s duty cycle can be used to power the company’s office building, before recharging overnight when electricity rates are at their cheapest. Gnewt is currently building a future roadmap to use the same technology to feed back into the grid itself at times of peak demand, effectively trading power at a profit by buying low and selling high.

A new data reality

Many of us are, by now, used to hearing about how businesses are saving money and finding better ways to operate by breaking down data silos, bringing business knowledge under one roof, and applying the right kind of analytical power to it. Rarely, however, is big data as united with the physical world as it is in fleet management.

Sam Clarke, the founder of Gnewt, commented that bypassing the software which comes with vehicles and charging stations and implementing a centralised platform has made the company a ‘smart, emission-free, commercially viable fleet solution equipped to scale’ which at this point is making smart, algorithmic charging decisions ‘on a scale potentially bigger than anyone else in the country or perhaps even the world’.

That, of course, beyond cost savings or new revenue streams, is the goal: transport businesses which can succeed and thrive without tailpipe emissions. By plugging fleets into the same kind of transformation which we have seen happening across IT over the last decade, data will be at the heart of achieving that goal.

David Savage, Regional Manager - UK & Ireland, Geotab

David is the Regional Manager, UK & IRE for Geotab, the World’s leader in IoT and connected vehicle technology. With over 2m worldwide subscriptions we are now also the world’s largest commercial telematics company.