Where was the PU19G number plate registered?

Vehicles with the PU19G prefix were first registered in Carlisle, Cumbria through official DVLA regional allocation tag PU.

What year was a PU19G registration plate released?

The PU19G series was issued during March 2019 to August 2019.

What is the MOT pass rate for PU19G vehicles?

Vehicles in the PU19G cohort demonstrate an average historical MOT pass rate of 80% based on 5 recorded DVSA inspections.

Batch Prefix Hub

PU19G Series Number Plates

UK vehicles registered in Carlisle, Cumbria during March 2019 to August 2019 with registration prefix PU19G.

Area Office: Carlisle (Carlisle, Cumbria)
Release Period: March 2019 to August 2019
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

AUDI 50% (1)

BMW 50% (1)

80%

Average MOT Pass Rate

Based on 5 historical tests

Common Colors

Blue1 vehicles

Silver1 vehicles

Active Plates in PU19G Series(2 of 2 displayed)

PU19GHS

MOT Valid

BMW 320

2.0L · Petrol · Blue

First Used: Dec 2019
MOT Expiry: 22 Jul 2027
Tax Status: —
Color: Blue

Check History & Specs

PU19GHY

MOT Valid

AUDI Q7

3.0L · Diesel · Silver

First Used: Jul 2019
MOT Expiry: 10 Aug 2027
Tax Status: —
Color: Silver

Check History & Specs

Reliability & Common Problem Guides for PU19G 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 PU19G Plates

Where was the PU19G number plate series registered?

Vehicles starting with PU19G 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 PU19G?

The PU19G age identifier corresponds to vehicles first registered between March 2019 to August 2019.

How can I check the MOT history of a PU19G 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.