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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.

With the increasing worldwide concern on environmental pollution, battery electrical vehicles (BEV) have attracted a lot attention. However, it still couldn’t satisfy the market requirements because of the low battery power density, high cost and long charging time. The range-extended electrical vehicle (REEV) got more attention because it could avoid the mileage anxiety of the BEVs with lower cost and potentially higher efficiency. When internal combustion engine (ICE) works as the power source of range extender (RE) for REEV, its NVH, emissions in starting process need to be optimized. In this paper, a 2-cylinder PFI gasoline engine and a permanent magnet synchronous motor (PMSM) are coaxially connected. Meanwhile, batteries and load systems were equipped. The RE co-control system was developed based on Compact RIO (Compact Reconfigurable IO), Labview and motor control unit (MCU).