Learning in MAP systems.

[Tony Bryant]

I understand how learning can be acheived in a MAF system (i.e. airflow range 
divided into buckets, a particular bucket pushed in the right direction when 
a oxy cross point is noticed)

What I don't yet fully appreciate is how can one practically acheive the same 
thing in a MAP system?  

It seems that since you now have fuelling tables with a 2D domain, instead of 
the 1D domain with MAF, you've got a hell of alot of buckets to learn in. 

What are some useful technqiues to make sure you don't end up with a map with 
a couple of learnt points and lots of default points?

Am I missing something obvious here?


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