Where was the UG11E number plate registered?

Vehicles with the UG11E prefix were first registered in the UK through official DVLA regional allocation tag UG.

What year was a UG11E registration plate released?

The UG11E series was issued during March 2011 to August 2011.

What is the MOT pass rate for UG11E vehicles?

Vehicles in the UG11E cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

UG11E Series Number Plates

UK vehicles during March 2011 to August 2011 with registration prefix UG11E.

Area Office: DVLA Region (UG)
Release Period: March 2011 to August 2011
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

FORD 50% (1)

NISSAN 50% (1)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Silver1 vehicles

White1 vehicles

Active Plates in UG11E Series(2 of 2 displayed)

Filter by 6th Letter:

UG11EEE

TaxedMOT Valid

NISSAN NV200

1.5L · Diesel · Silver

First Used: Jul 2013
MOT Expiry: 08 Jul 2027
Tax Status: Taxed
Color: Silver

Check History & Specs

UG11ENN

MOT Valid

FORD KUGA

2.0L · Diesel · White

First Used: Mar 2017
MOT Expiry: 02 Feb 2027
Tax Status: —
Color: White

Check History & Specs

Reliability & Common Problem Guides for UG11E Makes

Explore common mechanical faults, MOT advisory trends, and recall notices for popular vehicles in this registration batch:

FORD Common Problems NISSAN Common Problems

Frequently Asked Questions about UG11E Plates

Where was the UG11E number plate series registered?

Vehicles starting with UG11E were assigned to the DVLA regional office covering the UK. The first two letters (UG) identify the memory tag assigned by the DVLA.

What registration period is UG11E?

The UG11E age identifier corresponds to vehicles first registered between March 2011 to August 2011.

How can I check the MOT history of a UG11E vehicle?

Click any registration in the plate list above to view the complete DVSA inspection history, advisory alerts, mileage progression, road tax status, and our AI mechanical risk evaluation.