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For calibrating the vehicle model of a commercial vehicle dy- namics program a parameter estimation tool has been developed which relies on observations obtained from driving tests. The associated non- linear least-squares problem can be solved by means of mathematical op- timization algorithms most of them making use of first-order derivative information. While the complexity of the investigated vehicle dynam- ics program only allows the objective gradients to be approximated by means of finite differences, this approach enables significant savings in computational time when performing the additionally required evalua- tions of the objective function in parallel. The employed low-cost parallel computing platform which consists of a heterogeneous PC cluster is well suited for the needs of the automotive suppliers and industries employing vehicle dynamics simulations.

A Parallel Optimization Scheme for Parameter Estimation in Motor Vehicle Dynamics