Where was the TC53E number plate registered?

Vehicles with the TC53E prefix were first registered in the UK through official DVLA regional allocation tag TC.

What year was a TC53E registration plate released?

The TC53E series was issued during September 2003 to February 2004.

What is the MOT pass rate for TC53E vehicles?

Vehicles in the TC53E cohort demonstrate an average historical MOT pass rate of 88.9% based on 9 recorded DVSA inspections.

Batch Prefix Hub

TC53E Series Number Plates

UK vehicles during September 2003 to February 2004 with registration prefix TC53E.

Area Office: DVLA Region (TC)
Release Period: September 2003 to February 2004
Tracked in Batch: 2 vehicles
MOT Pass Rate: 88.9%

Popular Makes

MITSUBISHI 100% (2)

88.9%

Average MOT Pass Rate

Based on 9 historical tests

Common Colors

Blue1 vehicles

Brown1 vehicles

Active Plates in TC53E Series(2 of 2 displayed)

Filter by 6th Letter:

TC53EES

MOT Valid

MITSUBISHI L200

2.4L · Diesel · Blue

First Used: Sep 2015
MOT Expiry: 02 May 2026
Tax Status: —
Color: Blue

Check History & Specs

TC53EMC

MOT Valid

MITSUBISHI SHOGUN

3.2L · Diesel · Brown

First Used: Apr 2012
MOT Expiry: 15 May 2027
Tax Status: —
Color: Brown

Check History & Specs

Reliability & Common Problem Guides for TC53E Makes

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

MITSUBISHI Common Problems

Frequently Asked Questions about TC53E Plates

Where was the TC53E number plate series registered?

Vehicles starting with TC53E were assigned to the DVLA regional office covering the UK. The first two letters (TC) identify the memory tag assigned by the DVLA.

What registration period is TC53E?

The TC53E age identifier corresponds to vehicles first registered between September 2003 to February 2004.

How can I check the MOT history of a TC53E 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.