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Just so I understand the process:
Haltech/KP supplied a base map/maps, which consisted of a volumetric efficiency (VE) map and a target AFR map, right? I really haven't gotten into the software side too much. I am just trying to understand it. An AFR map should be based on rpms and MAP. The AFR map, as well as, the VE map are just conservative maps. A tuner would need to modify the AFR map and VE map based on the vehicle specifications. Maybe a turbocharged car will want to be a little richer than a NA car to avoid knock or something. Besides that, a tuner will modify ignition timing and cam timing to gain more power, right?
The short-term fuel trims adjust the fueling to hit the AFR targets, and the long-term fuel trims applies its corrections to the VE maps, which means the short-term fuel trims should make smaller and smaller adjustments, right? Basically with self-learning, the long-term trims are applied to the VE maps, right? If the AFR maps are conservative then self-learning will get the car closer to those values, but not necessarily optimize the car, or will it? Will self-learning modify the ignition timing or cams to optimize the power? No, right, because it doesn't know the power, but only AFR targets, right?
Sorry, I'm just trying to understand what self-learning does because I watched the Haltech video, and it didn't really answer my question.
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