Where was the TC16G number plate registered?

Vehicles with the TC16G prefix were first registered in the UK through official DVLA regional allocation tag TC.

What year was a TC16G registration plate released?

The TC16G series was issued during March 2016 to August 2016.

What is the MOT pass rate for TC16G vehicles?

Vehicles in the TC16G cohort demonstrate an average historical MOT pass rate of 100% based on 9 recorded DVSA inspections.

Batch Prefix Hub

TC16G Series Number Plates

UK vehicles during March 2016 to August 2016 with registration prefix TC16G.

Area Office: DVLA Region (TC)
Release Period: March 2016 to August 2016
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

FORD 50% (1)

NISSAN 50% (1)

100%

Average MOT Pass Rate

Based on 9 historical tests

Common Colors

Blue1 vehicles

White1 vehicles

Active Plates in TC16G Series(2 of 2 displayed)

Filter by 6th Letter:

TC16GAS

MOT Valid

FORD TRANSIT

2.0L · Diesel · White

First Used: Jan 2017
MOT Expiry: 12 Apr 2027
Tax Status: —
Color: White

Check History & Specs

TC16GTR

MOT Valid

NISSAN GT-R

3.8L · Petrol · Blue

First Used: Mar 2016
MOT Expiry: 21 Dec 2026
Tax Status: —
Color: Blue

Check History & Specs

Reliability & Common Problem Guides for TC16G 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 TC16G Plates

Where was the TC16G number plate series registered?

Vehicles starting with TC16G 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 TC16G?

The TC16G age identifier corresponds to vehicles first registered between March 2016 to August 2016.

How can I check the MOT history of a TC16G 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.