Where was the UH58E number plate registered?

Vehicles with the UH58E prefix were first registered in the UK through official DVLA regional allocation tag UH.

What year was a UH58E registration plate released?

The UH58E series was issued during September 2008 to February 2009.

What is the MOT pass rate for UH58E vehicles?

Vehicles in the UH58E cohort demonstrate an average historical MOT pass rate of 57.1% based on 7 recorded DVSA inspections.

Batch Prefix Hub

UH58E Series Number Plates

UK vehicles during September 2008 to February 2009 with registration prefix UH58E.

Area Office: DVLA Region (UH)
Release Period: September 2008 to February 2009
Tracked in Batch: 2 vehicles
MOT Pass Rate: 57.1%

Popular Makes

AUDI 50% (1)

BMW 50% (1)

57.1%

Average MOT Pass Rate

Based on 7 historical tests

Common Colors

White2 vehicles

Active Plates in UH58E Series(2 of 2 displayed)

Filter by 6th Letter:

UH58ERS

MOT Expired

BMW 420

2.0L · Diesel · White

First Used: Jan 2015
MOT Expiry: 03 Jul 2023
Tax Status: —
Color: White

Check History & Specs

UH58ETH

MOT Valid

AUDI A1

1.4L · Petrol · White

First Used: Sep 2018
MOT Expiry: 13 Feb 2027
Tax Status: —
Color: White

Check History & Specs

Reliability & Common Problem Guides for UH58E Makes

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

AUDI Common Problems BMW Common Problems

Frequently Asked Questions about UH58E Plates

Where was the UH58E number plate series registered?

Vehicles starting with UH58E were assigned to the DVLA regional office covering the UK. The first two letters (UH) identify the memory tag assigned by the DVLA.

What registration period is UH58E?

The UH58E age identifier corresponds to vehicles first registered between September 2008 to February 2009.

How can I check the MOT history of a UH58E 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.