---
title: "EV Fleet Utilisation in 2026: Why a 20% Electric Fleet Does Not Electrify 20% of Miles"
id: "27040"
type: "post"
slug: "ev-fleet-utilisation-electrified-mileage-gap-2026"
published_at: "2026-09-24T15:30:00+00:00"
modified_at: "2026-09-24T14:45:06+00:00"
url: "https://locus.sh/blogs/ev-fleet-utilisation-electrified-mileage-gap-2026/"
markdown_url: "https://locus.sh/blogs/ev-fleet-utilisation-electrified-mileage-gap-2026.md"
excerpt: "Electrified mileage share is decided by dispatch, not procurement. Modelling two depot archetypes shows the same 20% electric fleet delivering 12.2% or 25.9% of kilometres, and a regional operation stuck at an 8.5% ceiling however many vehicles it buys."
taxonomy_category:
  - "General"
---

#### [General](https://locus.sh/blogs/category/general/)

# EV Fleet Utilisation in 2026: Why a 20% Electric Fleet Does Not Electrify 20% of Miles

[Aseem Sinha](/author/aseem_locus/)

Sep 24, 2026

16 mins read

Electrified mileage share is the proportion of an operation’s kilometres actually driven on battery power, as distinct from the proportion of its vehicles that are electric. The two are rarely the same, because the vehicle that runs a route is chosen every morning against state of charge, route length and the dispatcher’s tolerance for risk, and those choices systematically send electric vehicles to shorter work. Buying electric vehicles sets the ceiling on electrified mileage; dispatch decides how much of that ceiling is reached. Locus, the world’s first Decision-Intelligent, Agentic TMS, matches vehicles to routes against range, charge state, payload and access rules in the same pass that builds the plan, which is where the gap is either closed or created.

## Key Takeaways

- In a modelled urban depot operation where range never binds, the same 20% electric fleet delivered 25.9% of kilometres under longest-route-first assignment and 12.2% under cautious shortest-route-first assignment, a difference of 2.12 times on identical assets.
- In a modelled regional operation, electrified mileage saturated at 8.5% and stayed there. Buying electric vehicles beyond 13% of the fleet added no electrified kilometres at all.
- The ceiling moves violently with usable range. Raising it from 180 km to 220 km lifted the regional ceiling from 8.5% to 30.9%, and 280 km lifted it to 82.3%.
- Arval’s 2021 testing at Millbrook found electric vans achieving 60% to 70% of claimed range in real use, so planning should treat a vehicle rated at 300 km as a 180 km to 210 km asset.
- Locus reasons across more than 250 real-world constraints including range, charge state and urban access, so vehicle-to-route matching is a planning output rather than a depot judgement call.

## Why Electrified Mileage Lags Fleet Share: The Business Case

The arithmetic gap exists because electric vehicles are assigned by range, and range sorts them onto shorter routes. Shorter routes carry fewer kilometres. So an electric share of the fleet converts into a smaller electric share of the distance unless assignment deliberately pushes the other way.

Rated range makes the gap worse than procurement assumes, because the number on the specification sheet is not the number available on a February morning with a full load. Arval’s testing at Millbrook Proving Ground, across three van sizes and multiple payloads in cold conditions, found that fleet operators should expect electric vans to achieve [60-70% of their claimed range in real-world use](https://www.fleetnews.co.uk/news/van-news/2021/05/13/arval-reveals-real-world-range-figures-for-electric-vans)
. That testing dates from 2021 and batteries have improved since, so treat the ratio as a planning floor rather than a current specification; the underlying causes, cold weather and payload, have not changed. On that basis a 300 km vehicle is a 180 km to 210 km asset, and every route between those figures and 300 km moves from eligible to ineligible.

Payload compounds it in both directions. Fuel and energy use are functions of mass, and the UK Government’s conversion factors methodology, drawing on the EU ARTEMIS project, shows the effect of vehicle loading on emissions being [linear with load](https://assets.publishing.service.gov.uk/media/66a9fe4ca3c2a28abb50da4a/2024-greenhouse-gas-conversion-factors-methodology.pdf)
. A heavily loaded electric vehicle draws down its usable range faster, so the routes it can take are shorter still on exactly the days the operation is busiest.

There is a reporting reason the gap goes unnoticed as well as an operational one. Under a tank-to-wheel boundary an electric vehicle reports zero, so every electrified kilometre looks like a complete elimination rather than a shift upstream to the grid. That makes the vehicle count feel like the meaningful number, because each conversion appears to remove a whole vehicle’s emissions regardless of how far it is actually driven. A well-to-wheel boundary, which corporate value chain reporting expects, removes that illusion and puts the question back where it belongs: how many kilometres, not how many vehicles.

The reason this matters more each year is that the denominator is growing. The World Economic Forum projects that without intervention [the number of delivery vehicles in the top 100 cities globally will increase by 36% until 2030, with emissions from delivery traffic rising 32%](https://www3.weforum.org/docs/WEF_Future_of_the_last_mile_ecosystem.pdf)
. An electrification programme measured in vehicles rather than kilometres will report progress against a target that is moving underneath it.

| Also Read: The CFO’s Guide to Green Fleet ROI: EV Cost Parity in Europe |
| --- |

## How the Gap Opens

### 1. Procurement sets a fleet share

A target is agreed as a percentage of vehicles, because that is how capital budgets, order books and depot charging infrastructure are all denominated. Nothing in that process references the distribution of route lengths.

### 2. Usable range is established, usually informally

The specification figure is discounted by some margin for weather, payload and battery ageing. Where that discount is a rule of thumb rather than a measurement, it will be wrong in the direction that matters.

### 3. Routes are built without reference to the fleet mix

Most planning creates routes first and assigns vehicles second. The route-length distribution is therefore fixed before anyone asks which of those routes an electric vehicle could serve.

### 4. Eligibility is determined by the longest route the vehicle can finish

A route is available to an electric vehicle only if its full length sits inside usable range, including stem distance back to the depot. This is a hard cut, not a preference, and it removes whole tranches of the distribution at once.

### 5. Assignment picks from the eligible set

Among routes an electric vehicle can serve, someone chooses which it actually gets. Sending it to the longest eligible route maximises electrified kilometres; sending it to the shortest minimises them and eliminates any risk of a stranded vehicle.

### 6. The result is reported as a fleet percentage

Progress is published as vehicles converted, which is the number procurement controls. Electrified mileage, which is the number that determines emissions, is rarely calculated at all.

| Also Read: Electric Vehicle Fleet Management: Complete Guide |
| --- |

## What the Model Shows

The model builds daily routes for two depot archetypes from stated inputs rather than observed customer data, using angular sweep clustering into balanced routes with nearest-neighbour sequencing and local search. The urban archetype serves a dense catchment and produces routes averaging 69 km with a maximum of 121 km. The regional archetype serves an urban core plus long rural spokes and produces routes averaging 230 km with a maximum of 378 km. Usable range is set at 180 km unless stated.

**Where range does not bind, the gap is pure policy.** In the urban archetype every route sits inside 180 km, so an electric vehicle could serve any of them. A 20% electric fleet nonetheless delivered 25.9% of kilometres under longest-eligible-first assignment, 20.0% under random assignment and 12.2% under shortest-first. The spread between the best and worst rule is 2.12 times, on the same vehicles running the same routes on the same day. That ratio held identically at every range tested from 120 km to 250 km, which confirms it is behavioural rather than physical.

**Where range binds, the ceiling is structural and low.** In the regional archetype only 13% of routes fall inside 180 km, and those routes carry 8.5% of total kilometres. Electrified mileage therefore saturates at 8.5%. At a 20% electric fleet it is 8.5%, at 30% it is 8.5%, and at 50% it is still 8.5%. Every vehicle bought beyond roughly 13% of the fleet has nowhere to go that adds a single electrified kilometre.

**The ceiling responds to range far more sharply than to fleet size.** Holding the regional operation fixed and varying only usable range, the mileage ceiling runs 3.1% at 150 km, 8.5% at 180 km, 30.9% at 220 km, 82.3% at 280 km and 99.1% at 350 km. A 22% increase in usable range, from 180 km to 220 km, multiplies the ceiling by 3.6. The non-linearity is not a quirk: the cliff sits around the median route length, because crossing it makes half the routes eligible at once and long routes carry disproportionate distance.

**This is why the specification sheet misleads.** With real-world range at 60% to 70% of claimed, a vehicle rated at 300 km lands at 180 km to 210 km usable, which on the regional distribution buys a mileage ceiling between 8.5% and 23.5%. A vehicle rated at 400 km lands at 240 km to 280 km usable and buys a ceiling between 50.9% and 82.3%. The procurement decision that looks like a marginal upgrade on the order form is the difference between a token programme and a real one, and the same spend on fewer, longer-range vehicles will usually electrify more distance than a larger order of shorter ones.

**The two archetypes need opposite interventions.** This is the practical consequence of running both. The urban operation does not need more vehicles or longer range, because range was never binding and the entire shortfall came from the assignment rule; its fix is a configuration change and a reporting metric. The regional operation cannot be fixed by assignment policy at all, because the eligible set is too small for the rule to matter; its fix is range specification, charging infrastructure or route redesign. Applying the wrong remedy to either is expensive, and the diagnostic that distinguishes them is the same route-length distribution both operations already hold.

**What the model does not settle.** It assumes one route per vehicle per day and no mid-shift charging. Opportunity charging, route splitting and depot swaps all raise the ceiling, and an operation with reliable charging at customer sites or on-route will do better than these figures. The point is not the specific ceiling but that one exists, is computable in advance from data the operation already holds, and is set by the route-length distribution rather than by the order quantity.

| Also Read: Route Optimisation in Europe: Urban Access Regulations |
| --- |

## Fleet Share and Mileage Share: Key Differences

| Dimension | EV share of fleet | EV share of kilometres |
| --- | --- | --- |
| Set by | Procurement and capital budget | Daily vehicle-to-route assignment |
| Changes | At order and delivery | Every morning |
| Determines | The ceiling | The realised emissions outcome |
| Limited by | Capital and charging infrastructure | Usable range against route lengths |
| Typical reporting | Published as programme progress | Rarely calculated |
| Improved by | Buying more vehicles | Assignment policy, range spec, route design |
| Failure mode | Buying past the ceiling | Cautious assignment to short routes |

## What to Look for in EV-Aware Dispatch

### Usable range as a measured value per vehicle

Range should be a live attribute reflecting state of charge, ambient temperature, payload and battery age, not a constant from the specification sheet. A platform applying rated range will build plans that fail in winter and, worse, a platform applying an over-cautious fixed discount will quietly refuse routes the vehicle could have run.

### Assignment that maximises electrified distance within the risk envelope

The default should be the longest eligible route rather than the shortest, with the safety margin stated explicitly rather than expressed as a habit. This is the single change that moved electrified mileage by 2.12 times in the model, and it costs nothing.

### Route building that is aware of the fleet it will be assigned to

Planning routes first and assigning vehicles second fixes the length distribution before eligibility is considered. A system that solves routing and vehicle assignment together can shape routes to fit the electric fleet rather than fitting the fleet to the routes.

### Electrified mileage reported as a first-class metric

If the only published figure is vehicles converted, nobody is accountable for the gap. The platform should report electrified kilometres as a share of total, alongside the theoretical ceiling, so the distance between them is visible.

### Range scenarios available before procurement

The ceiling as a function of usable range is computable from historical route data. A platform should be able to answer what a 250 km vehicle would electrify against last year’s routes, before the order is placed rather than after.

| Also Read: Sustainable Last-Mile Delivery: 2026 Enterprise Guide |
| --- |

## Vehicle-to-Route Matching in Practice

**A beverage distributor with depot-based mixed fleets.** Vans, trucks and motorbikes served thousands of small retail points a day, with more than an hour of spreadsheet planning before any vehicle moved and no single view of the fleet. After moving to planned assignment, fuel consumption fell 37% and orders per delivery trip rose 22%. A mixed fleet of three vehicle types is the same assignment problem as a mixed electric and diesel fleet, and it is solved with the same mechanism.

**A Fortune 50 parcel and logistics network.** More than a million freight shipments a year across 51 sites and a 4,500-strong driver pool, with each site measuring utilisation against its own plan. Centralising raised weekly execution from 75% to 92% and exposed more than $14M in unused capacity, including $565K at a single site. Utilisation measured locally hides exactly the mismatch between asset capability and work allocated that the electrified mileage gap is made of.

**A global FMCG distribution network.** Ten Asian countries, 1,000+ distributors and 5,000+ riders, with 12,000+ trips a month eliminated against $4B+ in optimised orders. Removing trips shrinks the denominator, which raises electrified mileage share without buying a single additional vehicle.

## Common Mistakes in Fleet Electrification Planning

**Setting the target as a percentage of vehicles.** Vehicles are what procurement controls, and kilometres are what emissions follow. A programme reporting fleet share can hit every milestone while electrified mileage stays flat, and nobody in the reporting chain will notice.

**Specifying range against the average route.** The average is the wrong statistic, because the ceiling is driven by how much total distance sits below the range threshold and long routes carry disproportionate distance. Specify against the upper percentiles of the distribution, in usable rather than rated terms.

**Letting dispatchers apply their own safety margin.** An unstated margin is applied inconsistently between depots and always in the cautious direction, which sends electric vehicles to the shortest work available. The margin should be a configured number that someone owns.

**Buying past the ceiling.** In the regional archetype every vehicle after roughly 13% of the fleet added zero electrified kilometres. Capital spent past that point buys compliance optics and nothing measurable, and the money would do more as range specification on fewer vehicles, or as depot charging that makes a second route per day possible. The ceiling is knowable before the order is placed, which makes overshooting it an avoidable error rather than an unlucky one.

| Also Read: TMS: Decarbonising the European Supply Chain |
| --- |

## How Locus Closes the Dispatch Gap

Locus, the world’s first Decision-Intelligent, Agentic TMS, solves routing and vehicle assignment in the same pass rather than in sequence, which is the structural requirement for closing this gap. The [route planning and dispatch layer](https://locus.sh/route-planning-system/)
 holds vehicle range, state of charge, payload, temperature zone, driver hours and urban access rules as first-class constraints across more than 250 real-world operating constraints, so an electric vehicle is matched to the longest route it can complete within a stated safety margin rather than the shortest route a planner feels comfortable giving it. Because routes and assignments are solved together, the plan can shape route lengths around the electric fleet instead of fixing the distribution first and discovering afterwards how little of it is eligible. Six governance mechanisms covering explainability, traceability, evaluation, autonomy levels, execution sandbox and human-in-the-loop record why each vehicle was assigned, and the [Control Tower](https://locus.sh/control-tower-software/)
 carries the executed record, which is what turns electrified mileage from an estimate into a measurement.

The platform reasons across those constraints over 1.5B+ deliveries for 360+ enterprise customers in 30+ countries at 99.99% uptime, with $320M+ in aggregate logistics cost savings, 800M+ miles reduced and 17M+ kg of CO2 avoided. Locus has been [recognised by Gartner for seven consecutive years](https://locus.sh/analyst-recognition/)
, including the 2026 Gartner Hype Cycle for Supply Chain Execution and Logistics Technologies and the 2026 Gartner Market Guide for Multicarrier Parcel Management Solutions, where ShipFlex is featured as a Representative Vendor. Locus holds Leader designation in the QKS SPARK Matrix for Transportation Management Systems 2025 and the #1 position for Route Planning in G2’s 2026 Best Software Awards. In October 2025, Ingka Investments, the investment arm of Ingka Group, the world’s largest IKEA retailer, acquired Locus. Locus continues to operate independently.

Two deployments show the assignment mechanism at work on mixed fleets. A [beverage distributor](https://locus.sh/case-studies/beverage-distributor-route-planning-dispatch/)
 running vans, trucks and motorbikes from depots to thousands of small retail points cut fuel consumption 37% and raised orders per delivery trip 22%, with route planning time down 35% and end-of-day reconciliation down 60%, after address validation pinned each retail point and vehicle types were matched to routes rather than allocated by habit. A [Fortune 50 parcel and logistics network](https://locus.sh/case-studies/fortune-50-parcel-centralized-dispatch/)
 running more than a million freight shipments a year across 51 sites lifted weekly execution from 75% to 92% and exposed more than $14M in capacity, at 99.99% uptime, once assignment was decided across the network rather than inside each depot. In both cases the assets were already owned and the gain came from deciding what they were given to do.

Owning electric vehicles sets a ceiling on electrified mileage; dispatch determines how much of it is reached, and the two numbers are routinely mistaken for one another. Modelling two depot archetypes put the same 20% electric fleet at either 12.2% or 25.9% of kilometres depending only on the assignment rule, and left a regional operation saturated at 8.5% however many vehicles it bought, with the ceiling swinging from 8.5% to 82.3% on usable range alone. The practical sequence is to compute the ceiling from your own route lengths before ordering, specify range against the upper percentiles in usable terms, then make longest-eligible-route assignment the default. Locus solves routing and vehicle matching together so that ceiling is reached rather than approached. [Request a Locus electrified mileage assessment](https://locus.sh/schedule-demo/)
 to see what your current fleet could be electrifying.

## Frequently Asked Questions

**Why does a 20% electric fleet not deliver 20% of miles?** Because electric vehicles are assigned by range, and range restricts them to shorter routes, which carry fewer kilometres. In the modelled urban operation a 20% electric fleet delivered 25.9% of kilometres under assignment that maximised electrified distance and 12.2% under cautious assignment to the shortest routes.

**What is electrified mileage share and why measure it?** It is the proportion of total kilometres actually driven on battery power, as opposed to the proportion of vehicles that are electric. Emissions follow kilometres rather than vehicle counts, so a programme tracking only fleet share can report steady progress while its emissions outcome does not move.

**How do you work out how many electric vehicles to buy?** Compute the share of total kilometres sitting on routes shorter than usable range, using historical route data. That share is the ceiling, and vehicles bought beyond the point that saturates it add no electrified mileage. In the modelled regional operation the ceiling was 8.5% and saturated at 13% of the fleet.

**How much range does a commercial electric vehicle really have?** Arval’s 2021 testing at Millbrook found electric vans achieving 60% to 70% of claimed range in real-world use across multiple payloads in cold conditions. Batteries have improved since, so treat that as a planning floor rather than a current figure, and size routes against usable range measured on your own vehicles.

**Does buying longer-range vehicles help more than buying more vehicles?** In the regional model, decisively. Raising usable range from 180 km to 220 km lifted the mileage ceiling from 8.5% to 30.9%, while raising fleet share past 13% at 180 km lifted it by nothing at all. The relationship is non-linear and the cliff sits near the median route length.

**Can route planning itself close the gap?** Partly. Solving routing and vehicle assignment together lets the plan shape route lengths around the electric fleet rather than fixing the distribution first, which raises the share of distance that falls inside range. Assignment policy alone moved electrified mileage by 2.12 times in the urban model without changing a single route.

MEET THE AUTHOR

Aseem Sinha

Vice President - Marketing

Aseem, leads Marketing at Locus. He has more than two decades of experience in executing global brand, product, and growth marketing strategies across the US, Europe, SEA, MEA, and India.

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## EV Fleet Utilisation in 2026: Why a 20% Electric Fleet Does Not Electrify 20% of Miles

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