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In low-temperature environment, heat supply requires considerable energy, which significantly increases energy consumption and shortens the mileage of electric vehicle. In the fuel cell vehicles, waste heat generated by the fuel cell system can supply heat for vehicle. In this paper, a thermal management system is designed for a the fuel cell interurban bus. Thermal management strategy aiming at temperature regulation for the fuel cell stack and the passenger compartment and minimal energy consumption is proposed. System model is developed and simulated based on AMESim and Matlab/Simulink co-simulation. Simulation results show that the fuel cell system can provide about 78 % energy of maximum heat requirement in -20 °C ambient temperature environment.

The lithium-ion battery plays an important role in saving energy and lowering emissions. Many parameters like temperature have an influence on the characteristic of the battery and this phenomenon becomes more serious in an electric vehicle. In this paper, the application of a boost DC/DC converter to the battery system of high power for online AC impedance identification is proposed. The function of the converter is to inject a current excitation signal into the battery at work and the normal output current is drawn by a load. Through analyzing the average state space equations and deriving the small signal model of the converter, the gain function is deduced of the fluctuated current signal against the fluctuated duty cycle which controls the converter. The control algorithm is designed and the system model is verified using Matlab/Simulink with respect to the disturbance current signal generation, the gain function and its variation with frequency range.

Pilot ignited natural gas diesel engine (PINGDE) was demonstrated to achieve low NOx emission, high fuel economy and low fuel cost. Despite of that, PINGDE is still confronted with problems such as high mechanical and thermal stress under heavy load, high CO and THC emission under small load and a trade-off relationship between NOx emission and fuel efficiency for whole operating points. In this study, tests were conducted to explore how three main variables including pilot injection timing, pilot diesel substitution rate and two kinds of pilot injection strategies influence the performance and emission of the modified WP10 engine. Two pilot injection strategies including pilot diesel injected once and twice were proposed and potential of promoting fuel economy and saving fuel cost was demonstrated. Moreover, a numerical engine model is established to optimize engine performance and emission with the help of MBC toolkit through limited experiments.

This study investigates the performance of a diesel engine fueled with naphtha under different load by varying injection parameters and exhaust gas recirculation (EGR) rate. The experiments were conducted on a 1.9-liter common rail diesel engine with a compression ratio of 17.5. Naphtha with a research octane number of 60.5 was tested. Three multi-injection strategies were designed. Each injection strategy, aided with EGR, conducts a characteristic combustion mode. Multi-injection strategies and single-injection strategy were tested and compared at one operating point under different main injection timing and EGR conditions. Results indicate that the well-designed multi-injection strategy has advantages over the single injection strategy in lowering noise, emissions and improving combustion efficiency. Among the three strategies, the strategy with 15-degree pilot timing and 2mg/cycle pilot injection could achieve both low NOx and PM emissions without sacrificing much fuel efficiency.

There is increasing demand for engine diagnostic and control with in-cylinder pressure signal. However, the application of cylinder pressure sensors are restricted by the high cost of the sensor. Another possible way for engine combustion state estimation is by processing of instantaneous crankshaft speed signal, but it is limited by the precision and complexity of the algorithm. It could be a solution by processing one cylinder pressure signal in combination with a crankshaft speed signal. The indicated torque could be estimated through engine speed processing and also from the measure cylinder pressure for the reference cylinder. Measurement results from experiments show that the indicated torque error traces of different cylinder are similar in shape. According to this assumption, the reference cylinder with cylinder pressure signal available can serve as both a parameter calibration information source and an error reduction measure.

Electric vehicle (EV) is a worldwide researching focus due to its environmental friendliness, but the inaccurate Remaining Driving Range (RDR) estimation hinders the EVs' popularity, and an accurate determination of the battery Residual Usable Energy (RUE) is the key factor to obtain a precise RDR value. A common RUE estimation method is based on State-of-Charge (SOC) estimation, in which the RUE is proportionally related to the current SOC. However, the battery voltage varies significantly under real-world conditions, and the traditional method results in certain estimation errors. An adaptive RUE prediction method (AEP) is introduced in this paper, in which the dynamic voltage is predicted based on the future discharge profile and a battery model, while the RUE is then calculated by the predicted voltage and current sequences.

This paper studies a control algorithm for fuel cell/battery city buses. The output power of the fuel cell is controlled by a D.C. converter, and the output ports of the converter and the battery are connected in parallel to supply power for the electric motor. One way to prolong service life is to have the fuel cell system to deliver a steady-state power. However, because of fluctuations in the bus voltage and uncertainness in the D.C. converter, the output power of the fuel cell system changes drastically. A closed-loop control algorithm is necessary to eliminate the errors between the output and target power of the fuel cell system. The algorithm is composed of two parts, the feed forward one and the feedback one. Influences of the bus voltage and D.C. efficiency are compensated automatically in the feedback algorithm by using a PI algorithm. The stability and robustness of the algorithm is analyzed.

In-cylinder pressure sensor, which provides the means for precise combustion control to achieve improved fuel economy, lower emissions, higher comfort, additional diagnostic functions etc., is becoming a necessity in future diesel engines, especially for chemical-kinetics dominated PCCI (Premixed Charge Compression Ignition) or LTC (Low Temperature Combustion) engines. In this paper, new control strategy is investigated to utilize in-cylinder pressure information into engine start process, in order to guarantee the success of engine start and in the meantime prevent penalty of fuel economy or pollutant emissions due to excessive fuel injection. An engine start acceleration model is established to analyze the engine start process. “In-cylinder Combustion Analysis Tool” (i-CAT), is used to acquire and process the in-cylinder pressure data and deliver the combustion indices to ECU (Engine Control Unit). Feedback control is accomplished in ECU based on this information.

Advanced compression ignition combustion system which reduces simultaneously both nitride oxides (NOx) and particulate matter (PM) is a promising approach to meet future emission regulations. In order to achieve advanced compression ignition, flexible fuel injection is required for ultra-early and post-TDC injections, which conventional injector fails to accomplish due to wall-wetting effect. In this work, special injectors with the spray angle of 60 degree are applied on a 4 cylinder mass-production diesel engine without modification of the engine configuration. For application-oriented study, sweep experiments of injection timings and durations, fuel injection pressure and the boost pressure are carried out to investigate the relationships between the control parameters and the engine performance. Model based calibration and real application tests validate the maximum applicable operation range of maximum speed of 2200 RPM and IMEP of 8.0 bar.

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.

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.

A vehicle control system basing on instantaneous energy optimization and series regenerative braking strategy was successfully developed for a fuel cell hybrid bus. The control system includes a vehicle control unit and other warning and measure systems. The control algorithm contains several blocks: start/stop, motor mode switch, diagnose and energy management. The movement of vehicle is divided into two parts: A) no braking process and B) braking process. An instantaneous equivalent hydrogen consumption optimization strategy was applied in process A. And in process B the braking energy was recovered partly so that the vehicle longitudinal dynamics would not be greatly affected. As a result, the fuel economy is improved from 9.6kg/100km to 7.9kg/100km in “China typical city bus cycle”.

Under the background of the increasingly serious global energy crisis and environmental problems, governments and enterprises around the world have paid more attention to the development of a new generation of green energy. The fuel cell city bus has become a favorite choice for new energy vehicles due to its free emission, high energy conversion efficiency as well as long driving endurance. A fuel cell city bus consists of varied components, such as fuel cell stacks, power batteries, DC/DC converter, electronic motor and etc. A distributed control system is developed for the fuel cell bus which has been facing many challenges from complex electromagnetic environment, demands of online monitoring and diagnosis, wide working temperature range, energy dynamic optimization (EDO) ability and etc. In order to meet the requirements of the challenges, a series of novel electronic technologies has been successfully implemented in the control system of the fuel cell city bus.

Classification of diagnosis knowledge for Common Rail System(CRS) was investigated in this paper. Main fault modes and judgement regulations of CRS were confirmed throng principle of expert system. A scan tool was designed to communicate with vehicle Electronic Control Unit(ECU), and data link between scanner and ECU was realized through K-line communication, moreover, diagnosis program was accomplished based on Key Word Protocol 2000(KWP2000). This study focused on methods to validate faults of CRS based on expert system. Method advanced was effective on fault diagnosis because expert system had capability of intellectual faculties. Finally, experiments were carried out on a six-cylinder diesel.

Many factors will influence injector's performance, and correlation among them is very complicated after experiments of Electronic-controlled Injector(ECI) were carried out. Equilibrium algorithm based on Self Adaptive Fuzzy Control(SAFC) was put forward to ensure consistency of injectors and remedy shortages of static compensation algorithm. Model of Common Rail System(CRS) was created under MATLAB/SIMULINK. It was showed by experiment results SAFC algorithm had good effects on reducing speed unevenness of each cylinder, and it was found that effect for reducing unevenness when speed was over 1600 rpm was not very remarkable compared with below 1000 rpm for the diesel used for experiments.

The high emission level during start-up process of common rail diesel engine is still a problem for ultra low emission control. For the map-based common rail system, engine start-up process goes through the initialization of injection and rail pressure build-up process, so the fuel injection status is not stable. Based on the analysis of the characteristics of rail pressure build-up, engine speed variety and exhausted smoke emission during engine start-up process, it is found that the injection parameters of the initial phase of engine start-up have large effects on the start-up time and smoke emission. To optimize the smoke emission, this paper makes a study on the methods of determining the injection parameters during start-up by means of well-phased investigation of engine speed and orthogonal bench test. The research is carried out on a 6-cylinder 7.8L turbocharged diesel engine equipped with a DENSO ECD-U2 common-rail system.