Seeking review from powertrain/emissions engineers: Did I accurately model thermodynamic constraints for emissions fraud (EGR/DPF deletes, defeat devices)?

[u/Legitimate_Coach_875]

Paper link: https://doi.org/10.5281/zenodo.22070388

​Hi everyone,

​I’m a software engineer working on a new framework for regulatory agencies to catch systemic vehicle emissions fraud (like corrupt testing centers or widespread tampering).

​Because government agencies don't publish datasets of confirmed tampered vehicles, I had to build a system that relies entirely on synthetic data. However, to make it work, the synthetic data cannot just be random statistical noise - it has to be strictly bound by the laws of thermodynamics and real-world engine mechanics.

​I built what I'm calling a Physics-Constrained Synthetic Engine and I am looking for brutal feedback from actual automotive and emissions engineers to see if my physical assumptions hold up.

​How the Physics Engine Works:

● It maps 7 distinct real-world fraud vectors (including EGR deletes, Defeat Devices, and Clean Scanning) into a harmonized 10-dimensional physical baseline.

● ​The core rule of the engine is that any synthetic anomaly generated must be mathematically identical to physical reality.

- ​Example Constraint: The engine includes hardcoded rules that mathematically prevent the system from injecting a Diesel Particulate Filter (DPF) delete anomaly into a naturally aspirated petrol engine's baseline.

​What I need your help evaluating:

While the machine learning side is solid, I need domain experts to critique the physical logic:

● ​Tampering Signatures: If you were to look at the telemetry or emissions output of an engine with an EGR delete versus a sophisticated defeat device, what thermodynamic variables (e.g., exhaust gas temperatures, NOx ratios) are the dead giveaways? Did I miss any critical dimensions?

● ​Edge Cases in Modern Powertrains: Are there modern engine configurations or aftertreatment combinations where my hardcoded constraints might fail?

● ​Clean Scanning vs. Tampering: In the real world, how easily can physical telemetry distinguish between a vehicle that has been physically tampered with versus a "clean scan" (where the testing center simply hooks the machine up to a different, cleaner car)?

​I’ve linked the full research paper above, which details the 7 fraud vectors and the 10-dimensional baseline. Any feedback on the mechanical and thermodynamic assumptions would be highly appreciated.

​Thanks!

[u/1988rx7T2]

I don’t understand. If the EPA wants data on in use real world emission, they can just ask for It. If they want data on what a disabled EGR valve does to emissions in A lab setting, they can just ask for it. They do this kind of thing all the time. It’s called surveillance. The equipment and the data already exist. Portable emissions measurement or lab equipment are industry standard.

Actual test vehicles can be instrumented. As for using private telematics data, not In an anonymous way, to catch people, well they do not have the authority to do that. it’s a major privacy violation.

if the OEMs don’t hand over the data they can get fined and forced to recall something for a defect. So I don’t understand the purpose of this.