[Diy_efi] 60-2 Toothwheel - Kalman Filter or ( EKF ) usage

Bruce A Bowling bbowling
Tue Apr 3 13:36:49 UTC 2007

In the MegaSquirt MS-II version, we have implemented a simple form of the kalman filter known as an "Alpha-Beta-Gamma Tracking Filter".


Note that this is just another form of a predictor-corrector algorithm. In fact, originally we implemented a full-blown kalman filter, but quickly realized that since all of the sample datapoints had the exact same statistical error the a-b-g filter implementation would suffice. Full-up KF are used to determine the best answer for the next state from many different sources of measurements (with corresponding variances) and process model sources. 

Tracking filters are used everywhere, from missle track determination, machine vision, to brushless commutation of DC motors. A side benefit is that they are extremely easy to implement and are not very computationally intensive - in fact they can be easily synthesized in programmable logic.

- Bruce

-----Original Message-----
>From: Mike <niche at iinet.net.au>
>Sent: Apr 3, 2007 8:58 AM
>To: diy_efi at diy-efi.org
>Subject: Re: [Diy_efi] 60-2 Toothwheel - Kalman Filter or ( EKF ) usage
>At 08:15 PM 4/3/07, you wrote:
>>I'm using a microcontroller with standard CAPTURE/COMPARE units in order to
>>process a 60-2 crank wheel. I'm very concerned about noise and a single step
>>Kalman Filter seems to be a very good tool for this application.
>Not sure what u mean by a "60-2" though if you are not using it for synchronism
>of fuel/ignition and only for a speed rpms derivation - albeit a good one then it might be ok.
>>Does anybody have experience with that? Could you please point me to some
>>articles or information on how that particular application of Kalman could
>>be implemented? Is it really efficient as it sounds like?
>Ive used a multistage kalman filter in a nucleonic ore flow gauge project where
>two Co60 beams and counters measured mass flow rate of ore by absorption.
>ie. Trying to data process two normal curves as they were affected by falling ore
>and gravity was my first foray into 16 bit micros in 1980 or so. It was a bit over
>my head but I struggled through it and we made the system work fine though we did
>bring in a specialist mathematician from India's mining industry to lend a hand, his
>command of english emabrrased us poor colloquial cohorts !
>They were reasonably effective and the various coefficients and post processing supplied a total
>flow rate that was within 1 to 3% *but* the short term accuracy was not better
>than 20% or so as the various state variables took many cycles to clear or rather
>'impose' their accumulations on the overall flow rate.
>In other words I feel it not appropriate to use Kalman for speed measurements
>and definitely nor for anything requiring any synchronicty at all under any circumstances.
>>I'm still reading the basic literature about Kalman and Statistics.
>it was tough for me 26 years ago,
>I think you wont need it if you can address the h/w issue with respect to noise such
>as cable routine, impedance of sensors, screening etc
>Eg. The Crank signal for the EFI and ignition for an RB30 motor is passed in parallel more
>or less with the spark wiring loom for a few cms, it might blow the odd sensor but doesnt seem to affect
>noise on a cycle by cycle basis. ie The ignition is smooth and stable for working
>sensors that dont get too hot...
>>Much appreciated.
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>Regards from
>Perth, Western Australia
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