A Neural Network Technique for Verification of Dynamometer Parasitic Losses

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.