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The dynamic and system reliability of driving system in battery electric vehicles (BEVs) highly depend on the fault diagnosis technology. In this paper, we provided a new data compression approach and validated it on a method based on neural network (NN) to detect both failures' types and degree in drive system. In time-/frequency domain several statistical features were extracted from signals acquired...
This paper presents a knee torque estimation in non-pathological gait cycle at stance phase. Comparative modelling by using dynamics model and neural network model is discussed. Dynamics modelling is constructed by using simple two degree of freedom dynamics with Newtonian calculation approach and more complex four degree of freedom dynamics with Lagrangian calculation approach. Neural network based...
In order to solve the problem of establishing the mathematic model for shield construction faults diagnosis, an approach to the mathematic model by using BP neural network is presented in this paper. The BP neural network model for diagnosing three familiar shield construction faults based on the data of shield excavation parameters was built. The inputs of the model are respectively nine shield excavation...
Aiming at the mass-energy power assembly control system in HEVs, a method is designed to estimate the engine torque, which is based on improved BP neural network. Based on the experiment results in engine dynamometer, and strong nonlinear characteristic of the engine is taken into account, traditional BP neural network error function is improved, and it is trained by optimal stopping, as a result...
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