Where was the PV14L number plate registered?

Vehicles with the PV14L prefix were first registered in Carlisle, Cumbria through official DVLA regional allocation tag PV.

What year was a PV14L registration plate released?

The PV14L series was issued during March 2014 to August 2014.

What is the MOT pass rate for PV14L vehicles?

Vehicles in the PV14L cohort demonstrate an average historical MOT pass rate of 77.8% based on 9 recorded DVSA inspections.

Batch Prefix Hub

PV14L Series Number Plates

UK vehicles registered in Carlisle, Cumbria during March 2014 to August 2014 with registration prefix PV14L.

Area Office: Carlisle (Carlisle, Cumbria)
Release Period: March 2014 to August 2014
Tracked in Batch: 2 vehicles
MOT Pass Rate: 77.8%

Popular Makes

FORD 100% (2)

77.8%

Average MOT Pass Rate

Based on 9 historical tests

Common Colors

Black1 vehicles

Yellow1 vehicles

Active Plates in PV14L Series(2 of 2 displayed)

PV14LEE

MOT Valid

FORD FOCUS

2.0L · Petrol · Yellow

First Used: Mar 2017
MOT Expiry: 13 Jul 2027
Tax Status: —
Color: Yellow

Check History & Specs

PV14LET

MOT Valid

FORD TRANSIT CUSTOM

2.0L · Diesel · Black

First Used: Mar 2019
MOT Expiry: 01 Apr 2027
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for PV14L Makes

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

FORD Common Problems

Frequently Asked Questions about PV14L Plates

Where was the PV14L number plate series registered?

Vehicles starting with PV14L were assigned to the Carlisle covering Carlisle, Cumbria. The first two letters (PV) identify the memory tag assigned by the DVLA.

What registration period is PV14L?

The PV14L age identifier corresponds to vehicles first registered between March 2014 to August 2014.

How can I check the MOT history of a PV14L 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.