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An online fault detection and isolation (FDI) method for several common sensor faults and even demagnetization of PMSM is proposed by combining model-based and signal analysis technology. To begin with, the field reconstruction method (FRM) of PMSM is employed to obtain the flux residuals which are used as the criterion of fault detection. Then, the flux residuals are transformed by multi sequence harmonic synchronous rotating transformation and inputted into low pass filters (LPFs) in order to obtain the DC components. Last, offset and gain faults of the two phase current sensors, offset fault of the rotor angle sensor and permanent magnet (PM) demagnetization can be isolated by comparing the DC components and preset thresholds. The detection and isolation strategy of PMSM is validated by motor controller hardware in motor bench tests.

The energy consumption depends not only on the structures of vehicles but also on their operating conditions. For vehicles with the same structure, the operating conditions will vary from driver to driver. In this paper, considering the difference of operating conditions, the concept of statistical energy consumption is proposed to reveal the statistical law of actual vehicle energy consumption. In this paper, a plug-in hybrid electric vehicle (PHEV) is taken as the research object. Based on the distribution law of three vehicle use factors, i.e. vehicle mass, daily driving distance and driving aggression, Monte Carlo method is used to simulate and calculate the statistical energy consumption and statistical comprehensive energy consumption. Then, the energy consumption values that only considered the daily driving distance is calculated.

Automotive embedded DCS is widely used to solve automotive control problems. This paper presents a model-driven development technology for such systems. Models of automotive embedded DCS are built up strictly complying with the four-layer-model architecture, which is presented by Model-Driven Architecture (MDA). Three kinds of models are used to describe the protocol data structure, the algorithm process and visualization aspects of automotive embedded DCS. Corresponding XML databases are created based upon these models. As a single data source, these databases play key roles in further development phases, including generating the protocol specification, MC&D systems and embedded programming, etc. Some demonstrative applications are presented in this paper.