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The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.

A great deal of effort has been directed towards Gasoline HCCI engines, which have the potential of providing better fuel economy and emission characteristics than conventional SI engines. For stable HCCI engine operation, cycle-by-cycle based closed-loop control is needed. Such a control scheme requires an accurate and reliable sensor to monitor the combustion and provide a feedback signal. At present, the general method used to measure the combustion parameters is to monitor in-cylinder pressure with a cylinder pressure sensor. However, using in-cylinder pressure transducers is not feasible for use in mass production of HCCI engines. A good substitute to get information about combustion is the knock sensor, which is already equipped on engines on a large scale. In this paper, the knock signal from an HCCI engine equipped with 4VVAS is analyzed in detail to find the relationship between the combustion parameters and the knock sensor signal.

The fuel economy of plug-in hybrid electric city bus (PHEV) is deeply affected by driving cycle and travel distance. To improve the adaption of energy management strategy, the equivalent coefficient of fuel is the key parameter that needs to be pre-optimized based on the predicted driving cycle. An iterative learning method was proposed and implemented in order to get the best equivalent coefficient based on the predicted driving cycle and battery capacity. In the iterative learning method, the energy model and kinematics model of the bus were built. The ECMS (Equivalent Consumption Minimization Strategy) method was applied to obtain the best fuel economy with the given equivalent coefficient. The driving paths and running time of city buses were relatively fixed comparing with other vehicles, and their driving cycle can be predicted by route content. The proposed optimized strategy was applied on the factory sets of plug-in hybrid electric city bus.

The spark-assisted compression ignition (SACI) is widely used to expend the high load limit of homogeneous charge compression ignition (HCCI), as it can reduce the high heat release rate effectively while partially maintain the advantage of high thermal efficiency and low NOx emission. But as engine load increases, the SACI combustion traditionally using negative valve overlap strategy (NVO) faces the drawback of higher pumping loss and limited intake charge availability, which lead to a restricted load expansion and a finite improvement of fuel economy. In this paper, research is focused on the SACI combustion using positive valve overlap (PVO) strategy. The characteristics of SACI combustion employing PVO strategy with external exhaust gas recirculation (eEGR) are investigated. Two types of PVO strategies are analyzed and compared to explore their advantages and defects, and the rules of adjusting SACI combustion with positive valve overlap are concluded.

Homogeneous charge compression ignition (HCCI) technology is promising to reduce engine exhaust emissions and fuel consumption. However, it is still confronted with the problem of its narrow operation range that covers only the light and medium loads. Therefore, to expand the operation range of HCCI, mode switching between HCCI combustion and transition SI combustion is necessary, which may bring additional problems to be resolved, including load fluctuation and increasing the complexity of control strategy, etc. In this paper, a continuously adjustable load strategy is proposed for gasoline engines. With the application of the strategy, engine load can be adjusted continuously by the in-cylinder residual gas fraction in the whole operation range. In this research, hybrid combustion is employed to bridge the gaps between HCCI and traditional SI and thus realize smooth transition between different load points.

Approximately 50% energy is consumed during the acceleration of a city bus. Fuel consumption during acceleration is significantly affected by driving behavior. In this study, 13 characteristic parameters were selected to describe driving style based on analysis of how driving influences fuel consumption during acceleration. The 100,000 km real-world vehicle running data of six drivers on three city buses in a particular bus line in Tianjin, China were sampled using a vehicle-on-line data logger. Based on the selected characteristic parameters and collected driving data, an evaluation model of the fuel consumption level of a driver was established by adopting the method of decision tree C4.5. For two-level classification, the model has over 85% prediction accuracy. The model also has the advantages of having a few training samples and strong generalization. As an example of the model application, the fuel-saving potential of a driver under optimal operations was analyzed.

Electrically assisted turbochargers are a promising technology for improving boost response of turbocharged engines. These systems include a turbocharger shaft mounted electric motor/generator. In the assist mode, electrical energy is applied to the turbocharger shaft via the motor function, while in the regenerative mode energy can be extracted from the shaft via the generator function, hence these systems are also referred to as regenerative electrically assisted turbochargers (REAT). REAT allows simultaneous improvement of boost response and fuel economy of boosted engines. This is achieved by optimally scheduling the electrical assist and regeneration actions. REAT also allows the exhaust turbine to operate within a narrow range of optimal vane positions relative to the unassisted variable geometry turbocharger (VGT). The ability to operate within a narrow range of VGT vane positions allows an opportunity for a more optimal turbine design for a REAT system.

The performance of three different electric turbo-compounding systems under both steady and driving cycle condition is investigated in this paper. Three configurations studied in this paper are serial turbo-compounding, parallel turbo-compounding and electric assisted turbo-compounding. The electric power, global gain of the whole system (engine and power turbine) under steady operating condition is firstly studied. Then investigation under three different driving cycles is conducted. Items including fuel consumption, engine operating point distribution and transient response performance are analyzed among which the second item is done based on statistic method combined with the results obtained under steady operating conditions. Study under steady condition indicates that electric assisted turbo-compounding system is the best choice compared with the other two systems. The performance of serial turbo-compounding is load oriented while parallel configuration is speed oriented.