Fleet decarbonisation involves a complex web of decisions. Maryam Farsi explores how digital twins could help fleet operators test different scenarios, understand the wider impact of their choices and find lower-risk, more cost-effective routes to zero emission vehicles
Fleet managers have so many decisions to make. How do we reduce emissions? What vehicles do we need? How could our operations be impacted? How much will it cost? Where do we start?
This is where digital twins can make a real difference. Digital twins are digital replicas of the physical world, and at UK research hub TransiT, we’re exploring how they can help to identify the lower-risk, more cost-effective pathways to transport decarbonisation in the UK across road, rail, air and maritime, for both passengers and freight.
In my own research for TransiT at Cranfield University, I’ve led the development of a standardised framework that can be used to design digital twins specifically to support transport decarbonisation.
This gives organisations developing digital twins a reference architecture – a practical step-by-guide guide. And we are now exploring how to apply this approach, with help from industry partners including global logistics group DHL and East Midlands Airport in Leicestershire.
What exactly is a digital twin?
The term “digital twin” is often used in discussions about artificial intelligence, smart cities and Industry 4.0, but the concept is actually quite straightforward.
In fleet operations, a digital twin might represent a single vehicle, an entire fleet, a depot, a charging network or even a complete logistics operation.
The digital twin receives information from vehicles, sensors, telematics systems, energy infrastructure and operational databases.
This creates a synchronised digital picture of what is happening across the fleet.
The key advantage of digital twins is their ability to exchange data both into and out of the physical world. This two-way interaction allows the twin to recommend or potentially trigger responses in the physical world as conditions change.
Think of it as a flight simulator for fleet management. Instead of experimenting in live operations, where mistakes can be costly, operators can explore different scenarios in a virtual environment first.
Why fleet decarbonisation is so difficult
Many fleet operators already have access to large amounts of data. Vehicle telematics, fuel reports, maintenance records, driver information and route data are widely available.
The challenge is that these datasets often sit in separate systems and are not easily integrated.
As our research found, many existing digital solutions focus on individual problems such as route optimisation, emissions monitoring or charging management. While these tools are useful, they often operate in isolation. This can make it difficult to understand the wider impact of operational decisions.
For example, a fleet manager may decide to electrify part of their fleet.
On paper, the decision may reduce tailpipe emissions. But it may also create new challenges around charging capacity, depot operations, vehicle scheduling and energy demand. Understanding these interactions is difficult using traditional planning tools.
Digital twins help by bringing all these factors together into a single environment.
Moving beyond vehicle replacement
One of the biggest misconceptions about transport decarbonisation is that it’s simply about replacing diesel vehicles with electric ones. In reality, decarbonisation is a system challenge.
Emissions are influenced by vehicle use, route planning, maintenance schedules, driver behaviour, energy sources, infrastructure capacity and operational processes. Changing one part of the system often affects another. A digital twin allows organisations to see these relationships clearly.
For example, instead of simply identifying the oldest diesel vehicles for replacement, a fleet manager can use a digital twin to help identify which vehicles generate the highest emissions, which routes may be best suited to electrification, and where charging infrastructure could deliver the greatest benefit.
How our digital twin framework works
Our research reviewed more than 100 studies from across the transport sector and combined this evidence with expert input from researchers and industry specialists. The result was a standardised digital twin framework designed specifically for transport decarbonisation and aligned with international standards.
Our framework consists of five main functional elements.
The first is observable elements. These are the physical things that need to be monitored, like vehicles, drivers, charging stations, depots, fuel use, infrastructure and operational processes.
The second is device communication. This is how data is collected from sensors, telematics systems, GPS devices, charging equipment and other connected assets.
The third is the core digital twin. This is where the intelligence sits. It creates digital representations of operations, runs simulations, analyses performance and generates forecasts and recommendations.
The fourth is the user layer, which allows fleet managers and operators to interact with the system through dashboards, reports, planning tools and decision-support applications.
Finally, there is the cross-system layer, which ensures different systems can work together securely and reliably. This includes data sharing, interoperability, cybersecurity and governance.
Together, these elements create a complete architecture for decarbonisation-focused decision making.
What this means for fleet managers
For fleet managers, the framework offers a structured blueprint for moving from data towards practical digital-twin design.
The first step is understanding what data already exists within the organisation.
Most fleets already collect valuable operational information. Vehicle locations, fuel consumption, charging records, maintenance schedules and driver performance data can all serve as inputs to a digital twin.
The next step is identifying decarbonisation objectives.
For some organisations, the priority may be reducing fuel use. For others, it may be supporting electric vehicle adoption, improving asset utilisation or meeting net-zero targets.
A digital twin helps translate these aims into measurable outcomes. For example, a fleet manager could use the twin to answer questions such as which routes should be electrified first, where charging infrastructure should be installed, and how vehicle replacement will affect operational performance.
A digital twin can also help answer questions such as how energy costs can be reduced while maintaining service levels and what the likely emissions impact of different investment options is.
Rather than relying on assumptions, managers can test multiple scenarios before committing resources.
Reducing risk and improving confidence
One of the most powerful benefits of digital twins is risk reduction.
Fleet decarbonisation requires significant investment. New vehicles, charging infrastructure, depot upgrades and software systems all involve financial commitment.
Decision-makers naturally want confidence that these investments will deliver value.
Digital twins provide an evidence-based way to explore alternative pathways.
An operator could compare different vehicle technologies, evaluate charging strategies or test changes to delivery schedules before implementing them in the real world.
This enables organisations to compare different pathways and identify potentially lower-risk and more cost-effective routes towards decarbonisation.
Preparing for a connected transport future
Looking ahead, transport systems are becoming increasingly connected.
Fleets will interact with energy networks, smart infrastructure, logistics platforms and wider supply chains. Decarbonisation decisions will increasingly depend on understanding these connections.
This is why our framework places such a strong emphasis on interoperability and cross-system integration.
The future will not be built around isolated technologies. It will depend on connected ecosystems where data flows securely between vehicles, operators, infrastructure providers and regulators.
Digital twins can provide an important foundation for this transition.
From data to action
The next steps for our digital twin blueprint include testing it in real-world operational settings, so we can see in practice how all that data supports decarbonisation decision-making.
My hope is that fleet managers and transport operators use the framework as a practical reference architecture and blueprint to guide the development of digital twins in a standardised, interoperable and scalable way.
Decarbonisation will still need investment, collaboration and long-term commitment. But digital twins can give organisations something that is often missing during major transitions: confidence.
Dr Maryam Farsi is a co-investigator at UK research hub TransiT and a senior lecturer in engineering optimisation at Cranfield University’s Centre for Digital and Design Engineering.
