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Based on the life cycle assessment method, this paper takes Shanghai taxi fleet as the research objective (traditional fuel vehicle (ICEV) and battery electric vehicle (BEV)). Under the condition of Shanghai energy structure, and combined with the actual application scenario of Shanghai taxi fleet, the study and prediction of carbon emission is carried out from three stages of manufacture, use and recycle. The research results show that: in the life cycle, under the current energy structure and battery technology of the taxi fleet in Shanghai, the carbon emission of BEV and ICEV will be at the same level at the mileage of 50,000 km. With the adjustment of energy structure, the progress of battery technology and the increase of the proportion of battery electric taxi fleet, the overall carbon emission of Shanghai taxi fleet will be reduced significantly.

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.

Based on the principle of carbon footprint, this paper selects typical passenger cars, such as internal combustion engine vehicles (ICEV), plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV) in the market of China as the research objects, and compares the energy consumption and carbon emissions of the three vehicle models in the whole life cycle for three major stages of manufacturing, driving and recycling in three representative cities. The results show that the manufacturing energy consumption of BEV is 5 times of HEV and 10 times of ICEV. For the BEV, only after driving a certain mileage it can be a less the unit energy consumption and emissions than ICEV. The whole life cycle carbon emissions of passenger cars with different power types is not only related to mileage, but also related to the energy structure of local electric power supply.

REEV (Range-Extended Electric Vehicle) can avoid the mileage anxiety of BEV (Battery Electric Vehicle). Nevertheless, RE (Range Extender) for passenger cars prefers to use ICE (Internal Combustion Engine) with smaller displacement and lower cylinder number, which is usually with a worse vibration performance at low speeds. As RE only outputs electricity, it provides the possibility to optimize NVH (Noise, Vibration, and Harshness) of the engine by PMSM (Permanent Magnet Synchronous Motor). By real-time control, the electromagnetic torque of PMSM can track the shaft torque fluctuation during engine strokes, especially the combustion stroke. When the instability and rolling torque of RE could be suppressed, NVH performance of RE can be improved. This paper presents simulation research on speed fluctuation suppression for RE engine based on dynamic torque compensation by controlling a PMSM.