Jonathan Maybin, Horiba Mira’s head of sales for vehicle attributes and performance, explains how cutting-edge automotive industry techniques are being used to answer some of the toughest questions in fleet management.

Now, more than ever, fleet operators face a challenging set of decisions. Top of the list for many is whether to switch to electric vehicles, but there are also complex questions around fleet management and total cost of ownership (TCO).

What makes these questions so difficult is that they are a step into the unknown. Even for fleets that have prior experience of running electric vehicles, the rapid evolution of technology in this area means that their capabilities and operating costs are changing – and the real-world figures don’t always tally with the official claims.

Horiba Mira has been at the forefront of automotive testing for more than 75 years. The biggest names in the motor industry come to us to understand the capabilities of their own vehicles and to benchmark those of their competitors. This gives us a unique ability to capture how a vehicle truly behaves – not just for any given scenario, but for the entirety of its lifecycle. And increasingly, this insight is being harnessed by fleet operators too.

The core of this approach is a software platform known as Mobius, which combines decades of engineering experience with cutting-edge AI technology to deliver quick and cost-effective insights. For instance, we use accelerated durability testing that can compress a vehicle’s entire lifetime into a period of six months – understanding how key factors such as the battery capacity degrade over that time and when parts are likely to require maintenance or replacement. This enables us to implement predictive maintenance, ensuring that the vehicles come off the road for short periods of scheduled downtime rather than costly emergency repairs.

We apply a similar methodology to analysing vehicle efficiency and energy usage. Testing carried out in facilities such as our proving ground and our climatic wind tunnel is combined with real-world data from the public road to map out the vehicle’s capabilities for its full operating range, including different weather conditions and driving styles.

This enables us to create a ‘digital twin’ of the vehicle, which can then be used to analyse how it will perform in any given scenario. For instance, we can look at energy usage across a delivery route and how this would vary if the traffic levels or weather conditions were to change.

The data we use to do this is all taken from real vehicles – either sourced by us or provided by the fleet – but we use a combination of AI and experience to pinpoint the most relevant aspects to test. That means we can build a highly accurate digital twin from a relatively small amount of data, without investing the time or the resources that would be required to test every single component. As a result, we can provide a practical tool for fleet operators that delivers a level of insight that was previously only available to engineers and vehicle manufacturers.

The results can be surprising. If you compare two different vans it’s entirely possible to find that one model has a more efficient powertrain, yet another may be cheaper to run overall as it consumes less energy for its heating, ventilation and cooling system. Similarly, one may perform better on the motorway, but another may be more efficient in stop-start traffic.

These virtual models can also be used to advise the driver in real-time via a display on the dashboard. By factoring in route planning, along with live traffic data and weather updates, the software can suggest ways to minimise fuel or battery consumption. For instance, if the system knows that there’s a stop line in 200 metres’ time, it might recommend that the driver begins coasting to reduce speed rather than applying the brakes.

The toolchains that we have developed for reducing fleet TCO also help to enable right-sizing in the fleet during procurement. Limitations on range and downtime due to charging mean that some operators may have to increase the size of their fleets to move to electric vehicles. But by how much? If you know the answer in advance you can provision accordingly, but if you underestimate the number of vehicles required it could lead to running a very expensive rental fleet to fill the shortfall.

Again, it’s not an easy question to answer. ICE vehicles are impacted by factors such as driving styles, traffic speeds and weather conditions, but the impact tends to be quite small – somewhere in the order of 2-4%. For electric vehicles, it can be far larger – often as much as 40%. By analysing vehicle energy usage and downtime we can replace this potentially costly guesswork with data insights.

In all these cases, it’s the data that empowers you to make better decisions. From choosing which vehicles to add to the fleet to knowing how many drops they will be able to cover when it’s rush hour and the temperature is sinking below freezing. Armed with this information, it’s possible to make better-informed decisions at an earlier stage, reducing the risks that come with new technology and maximising the benefits.