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To realize the precise control of injection and ignition of compressed natural gas engine, the 32-Digit PowerPC561 was selected as the single-chip microcomputer for the compressed natural gas engine. The signal processing module, controller module and power driver module of the engine control system were introduced successively. In the injection valve drive circuit, a new design method realized the ‘Peak&Hold’ drive current wave shape, which reduced the software work of injection development. In the ignition module circuit, the feedback of the time of ignition persistence and preliminary coil close period were successfully realized. The Engine Control Unit (ECU) has flexible control functions, which fulfill the requirements of engine control system.

Due to the high cost of torque sensors, a calculation model of transient torque is required for real-time coordinating control purpose, especially in hybrid electric powertrains. This paper presents a feedforward calculation method based on mean value model of turbocharged non-EGR diesel engines. A fitting variable called fuel coefficient is defined in an affine relation between brake torque and fuel mass. The fitting of fuel coefficient is simplified to depend only on three variables (engine speed, boost pressure, injected fuel mass). And a two-layer feedforward neural network is utilized to fit the experimental data. The model is validated by load response test and ETC (European Transient Cycle) transient test. The RMSE (root mean square error) of the brake torque is less than 3%.

A conventional vehicle with gasoline engine was tested on a chassis dynamometer over the new European drive-cycle (NEDC). The distributions of the engine speed and power, the throttle positions during the drive cycle are analyzed. Engine idling, acceleration and deceleration take an important proportion in the drive cycle. If engine idling is instead by engine stop, the fuel consumption will be improved by 2.27%. In an Integrated Starter Generator (ISG) system, with the assist of the starter/generator, transient operation of the engine will decrease, which reduces fuel consumption by 6%. Fuel economy will be also improved by braking regeneration and restricting operating points to an optimized region, the details are not discussed in this paper. To reduce fuel consumption further, the region where engine usually runs in urban traffic, should be paid more attention to while engine calibration.

As vehicle systems constantly grow in complexity and are subject to higher demands on performance, distributed control has become mainstream application in automotive industry. In a distributed control system, communication network connecting local controllers plays an important role. In this article, a fuel cell bus control system under development is introduced first. And then, traditional CAN and TTCAN network are analyzed for real-time performance respectively and TTCAN is chosen for its superiority. Subsequently, a TTCAN network is designed and implemented. Finally, a test platform for TTCAN network is devised and relevant platform experiments and on-board validation on the network are discussed.

The electronic control system of the variable nozzle turbocharger (VNT) was designed. The actuator is the electro-hydraulic servo proportional solenoid. The signals of the engine pedal position sensor, the engine speed sensor, the boost pressure sensor, the intake air temperature sensor, and the ambient pressure sensor are sampled and filtered. The engine working condition is estimated. The control algorithm was designed as the closed-loop feedback digital PI control together with the open-loop feed forward control. The gain-scheduled PI control method is applied to improve the robustness. The control system was calibrated at the turbocharger test bench and the engine test bench. The results indicate the designed control system has good performance for the boost pressure control under the steady and transient conditions.

At first, the dynamic electromagnetic characteristics of a pulsed solenoid valve is analyzed by experiments. The fast valve response is obtained by material modifications. Then, the intelligent solenoid driving method is discussed. The new techniques of the “active” PWM and the “d2i/dt2” detection are developed for feedback control of the solenoid holding current and the valve closure timing. Finally, the control and diagnosis method for the valve closure duration is investigated. A sensing mechanism utilizing momentary camshaft speed fluctuations of fuel injection pump is presented, which provides the basis for feedback control and diagnosis of the valve closure duration and diesel fuel injection process.