Engine makers: calibration staff, exhaust states, gas engines
Why engine makers struggle to calibrate and control engines with unmeasured catalyst states and few specialists, and how to check a model first.
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The state of the exhaust catalyst is not measured
What happens. Exhaust after-treatment is dosed and heated by maps. Inside the catalyst, how much it has stored, how aged it is and how hot each part is are not measured; only inlet and outlet sensors are available, and they lag.
What it costs. Emission limits are met with margin, which costs fuel and dosing agent. When a limit is tightened or the catalyst ages, the maps are re-done and conformity tests are repeated.
Why the usual fix fails. A second sensor shows one more point. Wider margins on dosing meet the limit but waste agent and fuel, and a map built for a new catalyst is wrong for an aged one.
How a fixed-price remote diagnosis checks it. From test-bench and drive-cycle logs I estimate the catalyst states from the signals you already record. The fixed-price remote diagnosis tells you whether a computed state can steer the dosing and what test data would be needed to trust it.
Background: Computing unmeasured states for control
Small engine makers lack calibration staff
What happens. A small engine maker has one or two people who know how to calibrate an engine on the test bench, and often none who can build a model. Every new variant or emission rule queues for the same person.
What it costs. Calibration takes bench time and expert time that a small company cannot easily spare. Launches slip, and engines ship with conservative settings that cost power and fuel.
Why the usual fix fails. Hiring a calibration engineer is slow and the work is uneven; outsourcing everything to a large service provider is expensive and the knowledge does not stay in the house.
How a fixed-price remote diagnosis checks it. I look at your bench data and the maps in use and ask which parameters really need to be measured and which a model can supply. The fixed-price remote diagnosis shows whether model-based calibration with a smaller test plan would work for your engine, and what you would do yourselves afterwards.
Background: Replacing hand-tuned parameter tables by a model
Control of gas engines needs scarce specialists
What happens. Gas engines run on fuels that vary and in operation modes that change with the grid: part load, fast ramps, island operation. The engine controller must hold knock limits and emissions while the load moves.
What it costs. Teams building engine management for gas engines find it hard to fill these roles. Controls get less development time than the engine hardware, and the engine runs with margin instead of at its limits.
Why the usual fix fails. A map-based controller needs a new calibration for each gas quality and each engine. More margin protects the engine but costs efficiency and emissions.
How a fixed-price remote diagnosis checks it. From engine logs (load, ignition timing, air and gas flows, knock and emission readings) I check which model of the engine is good enough to run the control. The fixed-price remote diagnosis tells you whether model-based engine control is likely to hold your limits at lower margin, and what it takes to test it.
Background: Predictive control of industrial processes
Engine control needs physical models and calibration together
What happens. Modern engine control combines models of air path, combustion, heat and exhaust with calibration on the bench. The people who build the models and the people who calibrate often sit in different teams and speak different languages.
What it costs. The cost is calibration effort repeated for each variant, and functions that behave well on the bench but not across the real range of conditions.
Why the usual fix fails. Adding people to calibration treats the symptom. A pure simulation model that nobody has fitted to bench data is not trusted, and a map that nobody can explain cannot be adapted.
How a fixed-price remote diagnosis checks it. I look at your bench measurements and the existing models to see how well they agree and where they diverge. The fixed-price remote diagnosis tells you whether a model-based control and calibration chain is realistic for your engine family, and what to fit first.
Background: Replacing hand-tuned parameter tables by a model
More problems that concern this industry
These problems are described on the page of the industry where they matter most:
- Calibrating control maps takes weeks of bench time (Test-bench makers)
- Thousands of map parameters are calibrated for every variant (Test-bench makers)
- A new fuel-cell or hydrogen powertrain needs its control concept from scratch (Fuel-cell system makers)
- Control and protection design for gas-turbine auxiliaries lacks specialists (Power and heat plant operators)
- Engine and generator models should define normal behaviour and flag deviations (Shipping and marine operators)
- Range-extender control needs people who know energy management (Automotive suppliers)
Check it on your plant first: a fixed-price remote diagnosis
EUR 4,500 net · 5 working days · remote · availability on request · freelance or through temporary agency work
Within a fixed scope and at a fixed price, I review your data, control structure and measurements remotely and tell you whether the problem on this page is behind your symptoms and what fixing it would take. You get a short summary for decision-makers and a technical report for your engineers.