Where was the TN17N number plate registered?

Vehicles with the TN17N prefix were first registered in the UK through official DVLA regional allocation tag TN.

What year was a TN17N registration plate released?

The TN17N series was issued during March 2017 to August 2017.

What is the MOT pass rate for TN17N vehicles?

Vehicles in the TN17N cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

TN17N Series Number Plates

UK vehicles during March 2017 to August 2017 with registration prefix TN17N.

Area Office: DVLA Region (TN)
Release Period: March 2017 to August 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

FORD 50% (1)

LAND ROVER 50% (1)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Black2 vehicles

Active Plates in TN17N Series(2 of 2 displayed)

Filter by 6th Letter:

TN17NER

MOT Valid

LAND ROVER RANGE ROVER VELAR

2.0L · Diesel · Black

First Used: Nov 2018
MOT Expiry: 26 Mar 2027
Tax Status: —
Color: Black

Check History & Specs

TN17NOW

MOT Valid

FORD RANGER

3.2L · Diesel · Black

First Used: Mar 2017
MOT Expiry: 27 Sep 2027
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for TN17N Makes

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

FORD Common Problems LAND ROVER Common Problems

Frequently Asked Questions about TN17N Plates

Where was the TN17N number plate series registered?

Vehicles starting with TN17N were assigned to the DVLA regional office covering the UK. The first two letters (TN) identify the memory tag assigned by the DVLA.

What registration period is TN17N?

The TN17N age identifier corresponds to vehicles first registered between March 2017 to August 2017.

How can I check the MOT history of a TN17N 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.