Where was the PU09N number plate registered?

Vehicles with the PU09N prefix were first registered in Carlisle, Cumbria through official DVLA regional allocation tag PU.

What year was a PU09N registration plate released?

The PU09N series was issued during March 2009 to August 2009.

What is the MOT pass rate for PU09N vehicles?

Vehicles in the PU09N cohort demonstrate an average historical MOT pass rate of 70% based on 10 recorded DVSA inspections.

Batch Prefix Hub

PU09N Series Number Plates

UK vehicles registered in Carlisle, Cumbria during March 2009 to August 2009 with registration prefix PU09N.

Area Office: Carlisle (Carlisle, Cumbria)
Release Period: March 2009 to August 2009
Tracked in Batch: 2 vehicles
MOT Pass Rate: 70%

Popular Makes

PEUGEOT 100% (2)

70%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

White2 vehicles

Active Plates in PU09N Series(2 of 2 displayed)

Filter by 6th Letter:

PU09NAT

MOT Valid

PEUGEOT 208

1.6L · Petrol · White

First Used: Mar 2016
MOT Expiry: 20 Jun 2027
Tax Status: —
Color: White

Check History & Specs

PU09NOD

MOT Valid

PEUGEOT PARTNER

1.6L · Diesel · White

First Used: Mar 2009
MOT Expiry: 14 Sep 2026
Tax Status: —
Color: White

Check History & Specs

Reliability & Common Problem Guides for PU09N Makes

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

PEUGEOT Common Problems

Frequently Asked Questions about PU09N Plates

Where was the PU09N number plate series registered?

Vehicles starting with PU09N were assigned to the Carlisle covering Carlisle, Cumbria. The first two letters (PU) identify the memory tag assigned by the DVLA.

What registration period is PU09N?

The PU09N age identifier corresponds to vehicles first registered between March 2009 to August 2009.

How can I check the MOT history of a PU09N 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.