Where was the PW16H number plate registered?

Vehicles with the PW16H prefix were first registered in Carlisle, Cumbria through official DVLA regional allocation tag PW.

What year was a PW16H registration plate released?

The PW16H series was issued during March 2016 to August 2016.

What is the MOT pass rate for PW16H vehicles?

Vehicles in the PW16H cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

PW16H Series Number Plates

UK vehicles registered in Carlisle, Cumbria during March 2016 to August 2016 with registration prefix PW16H.

Area Office: Carlisle (Carlisle, Cumbria)
Release Period: March 2016 to August 2016
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

AUDI 50% (1)

BMW 50% (1)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Grey1 vehicles

White1 vehicles

Active Plates in PW16H Series(2 of 2 displayed)

PW16HTE

MOT Valid

BMW 420

2.0L · Petrol · White

First Used: Apr 2019
MOT Expiry: 20 Aug 2027
Tax Status: —
Color: White

Check History & Specs

PW16HTY

MOT Valid

AUDI Q3

1.4L · Petrol · Grey

First Used: Jun 2018
MOT Expiry: 19 Aug 2027
Tax Status: —
Color: Grey

Check History & Specs

Reliability & Common Problem Guides for PW16H 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 PW16H Plates

Where was the PW16H number plate series registered?

Vehicles starting with PW16H were assigned to the Carlisle covering Carlisle, Cumbria. The first two letters (PW) identify the memory tag assigned by the DVLA.

What registration period is PW16H?

The PW16H age identifier corresponds to vehicles first registered between March 2016 to August 2016.

How can I check the MOT history of a PW16H 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.