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In this paper, a low-speed pre-ignition (LSPI) diagnostic strategy is designed based on the ion current signal. Novel diagnostic and re-injection strategies are proposed to suppress super-knock induced by pre-ignition within the detected combustion cycle. A parallel controller system that integrates a regular engine control unit (ECU) and CompactRIO (cRIO) from National Instruments (NI) is employed. Based on this system, the diagnostic and suppression strategy can be implemented without any adaptions to the regular ECU. Experiments are conducted on a 1.5-liter four-cylinder, turbocharged, direct-injected gasoline engine. The experimental results show two kinds of pre-ignition, one occurs spontaneously, and the other is induced by carbon deposits. Carbon deposits on the spark plug can strongly interfere with the ion current signal. By applying the ion current signal, approximately 14.3% of spontaneous and 90% of carbon induced pre-ignition cycles can be detected.

Plug-in hybrid electric vehicles (PHEVs) provide significantly improvement in fuel economy over conventional vehicles as well as reductions in greenhouse gas and petroleum. Numerous recent reports regarding control strategy, power train configuration, driving pattern, all electric range (AER) and their effects on fuel consumption and electric energy consumption of PHEVs are reported. Meanwhile, the control strategy for engine start-stop and mileage between recharging events from the electricity grid also has an important influence on the petroleum displacement potential of PHEVs, but few reports are published. In this paper, a detailed simulation model is set up for a plug-in series hybrid electric vehicle (PSHEV) employing the AVL CRUISE. The model was employed to predict the AER of the baseline PSHEV using rule-based logical threshold switching control strategy.

In this paper, based on the plug-in series hybrid electric vehicle development project, the vehicle technology solutions and the match of power system parameters were analyzed. The vehicle control strategies were identified and optimized according to plug-in hybrid vehicle features. The plug-in series hybrid, rule-based logic threshold switching control strategy, charge depleting (CD) mode and charge-sustaining (CS) mode are chosen according to the key factors, such as the environment, performance requirements, technical requirements and cost. And then the structure and model of vehicle control strategy were established to carry out vehicle energy management and power system control. The parameter selection, electric drive system matching, energy storage system design based on the requirement of vehicle performance, system architecture and control strategy are presented.