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The road load simulation control of a multi roll chassis dynamometer is augmented to include the effect of cornering. When the dynamometer is controlled to simulate a vehicle moving in a straight line the road load force is partitioned evenly so that the wheels may travel with identical speed. When control equations are slightly modified to allow an arbitrary partition of the road load force the wheels will move at different speeds. The force partitioning may be modified by taking into account factors of wheel base, inter axel distance and cornering steer angle so that the wheel speeds manifest the effect of cornering or the effect of tyre deflation.

An on line method for verification of chassis dynamometer operation uses a neural network. During the testing of a vehicle, it is assumed that after a warm up period the parasitic losses remain stable. There is normally no provision for verification of correct dynamometer operation while the test is running. This technique will detect if a component wears or fails during the testing of a vehicle and thus avoid testing under erroneous conditions. A Learning Vector Quantization (LVQ) neural network is trained to recognise poor dynamometer operation in order to signal a fault condition to the operator.