2022 Lotus Unknown 3.5L Petrol · AU22 BUO
2022 Lotus Unknown (3.5L, petrol). First registered 01/05/2022. Recorded mileage 21,667 miles. MOT status: Expired. Currently declared SORN.
- Make & Model
- LOTUS UNKNOWN
- Year / Origin
- 2022 · Norwich
- MOT Status
- Valid until 29/04/2026
- Road Tax
- SORN
- Recorded Mileage
- 21,667 mi
- ULEZ Compliance
- ULEZ Compliant (Euro 4+)
- Fuel & Engine
- Petrol · 3.5L
- Reliability Guide
- Common Faults
- Fuel Type
- Petrol
- Year
- 2022
- Engine
- 3456cc
AI-generated interpretation of this vehicle’s MOT record — not an official statement and not a substitute for an independent inspection.
AU22 BUO Key Findings
- 1 MOT test recorded
- Latest MOT passed on 24/04/2025
- 21,667 miles recorded at latest MOT
- No defects recorded at the latest MOT
Derived directly from the recorded DVSA and DVLA data shown on this page.
MOT Roadworthiness: Average
This rating reflects historical MOT pass rates and recurring advisory wear patterns from official DVSA test logs. Note that roadworthiness does not verify outstanding finance, insurance write-offs, or stolen records.
Verify lender finance agreements, insurance write-offs, police stolen registers, and mileage rollback.
Technical Specifications
Core Specifications
Identification & Status
Dimensions & Weights
Diagnostic & Valuation Intelligence
Estimate current market value
Generate an instant valuation benchmark based on live market listings, vehicle mileage, and recent dealer auction figures.
AU22 BUO MOT History
Interpretation generated from the recorded test data above — not an official DVSA statement and not a substitute for an independent inspection.
1 MOT test are recorded for this 2022 Lotus Unknown (AU22 BUO) between April 2025 and April 2025.
The record contains 1 pass and 0 failures.
The record shows no MOT failures, although 0 advisory notices note items to monitor.
Buyer's Guide & Inspection Advisory
Expert automotive synthesis from historical MOT defect records and market benchmarks.
Our Verdict
This 2022 Lotus presents a low-risk purchase due to its clean MOT history and low mileage, but limited model-specific data requires caution. A pre-purchase inspection is strongly recommended.
Prioritize checking for a full service history and verifying the 21,667-mile reading against the vehicle's age. Look for any unrecorded maintenance or modifications. Negotiate based on the lack of model-specific reliability data, and consider a third-party pre-purchase inspection to assess condition. Be wary of potential premium pricing due to the Lotus brand and yellow colour, which may affect resale.
Fuel economy for a 3.456L petrol engine is likely average to poor, with estimates around 25-30 mpg. Tax is likely £0 (2022 model), but insurance group will be high due to the engine size. Maintenance costs may exceed average due to Lotus's premium positioning. Estimated annual running cost: £1,200-£1,500, including fuel, insurance, and servicing.
Focus on the 3.456L engine for signs of wear, leaks, or unusual noises. Check suspension and brakes, as these are critical for performance-focused models. Verify the VIN against the registration documents to confirm no prior damage or fraud. Inspect the yellow paint for inconsistencies or repairs, and ensure all electronics (e.g., infotainment) function correctly.
The vehicle has a clean MOT record with 21,667 miles (below average for its age) and no recorded defects. However, the 'UNKNOWN' model designation and lack of aggregate reliability data mean buyers should verify service history and conduct a thorough inspection. Its 3.456L petrol engine suggests higher running costs compared to smaller models.
No aggregate MOT data available for this model, making it difficult to assess long-term reliability. Buyers should rely on individual vehicle history and inspections.
Reviewed by the IsItAGoodCar editorial team — Verified automotive analysis synthesized from official vehicle registries.
Data Sources
DVSA
Official MOT test logs & failure reasons
DVLA
Tax, registration & powertrain specs
Experian
Finance, stolen markers & total loss
AI Analysis
Historical fault & advisory patterns
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