find anything about this, so maybe i can post it all the same :)
Please somebody help me or point me on some ras archive i didnt find.
So i have probleme modeling differential.
Lets start with an open differential :)
lets assume those datas
TorqueIn .. torque given to the diff
TorqueOut[2] .. torque out of the diff to the both axles
ResistiveTorque[2].. torque that come back from axles
When reading books i can read that an open diff split torque_in in 2 to
the TorqueOut[i].
So TorqueOut[i] = TorqueIn / 2
Its also say ( Race Car Vehicules Dynamics page 734 ) "if one wheel
loses traction the total drive force available will be just twice the
force available from the tire with least grip". i.e. ResistiveTorque is
weak ?
So i modify to
TorqueMaxPossible = Min( ResistiveTorque[0], ResistiveTorque[1] )
Torque = Min( TorqueIn, TorqueMaxPossible )
TorqueOut[i] = Torque / 2
The probleme is when the driving wheels are not sliding at all ( i.e.
slip ratio ~0 ) the ResistiveTorque is almot zero , so TorqueOut[i]
become slower, so slipratio become slower, etc... the car doesnt accell
anymore :(
So what should i do ?
1) Always use Torque = TorqueIn ?
2) Use Torque = Min ( TorqueIn, TorqueMaxPossible ) only if
Abs(SlipRatio ) > 1 ( if we assume SlipRatio is normalize with Optimum
Slipratio ).
3) Maybe i should use a ResistiveBiasInstead ? TorqueBias =
ResistiveTorque[Grippy] / ResistiveTorque[Slippy] ? How should i use it
then ?
Limited Slip Diff
Ok, one i'll get Open Diff working , i think limited Diff are easy.
lets assume
OmegaOut[2] are angle velocity of axles
OmegaIn are anglular velocity Engine side
OmegaS , angulare velocity of internal diff
OmegaIn = ( OmegaOut[0] + OmegaIn[1] ) / 2
OmegaS = OmegaOut[1] - OmegaOut[2]
Td = Differential torque.
Torque = ?? , depend of how its works with open diff lets assume we have
2 grippy wheels
Torque = TorqueIn
Td = OmegaS * DiffFriction
TorqueOut[0] = ( Torque - Td ) / 2
TorqueOut[1] = ( Torque + Td ) / 2
Is that right ?
Now, should i clamp Td so Abs( Td ) is not > to Torque ??
thanks in advance for any help.
Seb.