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Sensors are critical for the monitoring and real-time control of fuel cell system, according to the reliability requirements of multi-sensor of 60kW automotive fuel cell system designed by our group, a two-level neural networks based fault diagnosis method is put forward in this paper. The two-level neural networks include a main net and five sub nets which(More)
In order to achieve the intelligent and automation AC charging of EV-Charging Station plug-in electric vehicles, a solution based on ZigBee technology is proposed that Communication between electric vehicle on-board charger and AC charging spot. The hardware system use TI's CC2480 RF chips as core components. This paper focuses on the studying for the(More)
This paper presents a neural network predictive control strategy to optimize oxygen supply for a proton exchange membrane fuel cell system. We propose using a time varying and local linearization auto-regressive moving average with exogenous (ARMAX) to model the nonlinear system, and employing recurrent neural network to estimate coefficients of the ARMAX(More)
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