Variable geometry turbocharger and exhaust gas recirculation valves are widely installed on diesel engines to allow optimized control of intake air mass flow and exhaust gas recirculation ratio. The positions of variable geometry turbocharger vanes and exhaust gas recirculation valve are predominantly regulated by dual-loop proportional–integral–derivative controllers to achieve predefined set-points of intake air pressure and exhaust gas recirculation mass flow. The set-points are determined by extensive mapping of the intake air pressure and exhaust gas recirculation mass flow against various engine speeds and loads concerning engine performance and emissions. However, due to the inherent nonlinearities of diesel engines and the strong interferences between variable geometry turbocharger and exhaust gas recirculation, an extensive map of gains for the P, I, and D terms of the proportional–integral–derivative controllers is required to achieve desired control performance. The present simulation study proposes a novel fuzzy logic control scheme to determine appropriate positions of variable geometry turbocharger vanes and exhaust gas recirculation valve in real-time. Once determined, the actual positions of the vanes and valve are regulated by two local proportional–integral–derivative controllers. The fuzzy logic control rules are derived based on an understanding of the interactions among the variable geometry turbocharger, exhaust gas recirculation, and diesel engine. The results obtained from an experimentally validated one-dimensional transient diesel engine model showed that the proposed fuzzy logic control scheme is capable of efficiently optimizing variable geometry turbocharger and exhaust gas recirculation positions under transient engine operating conditions in real-time. Compared to the baseline proportional–integral–derivative controllers approach, both engine’s efficiency and total turbo efficiency have been improved by the proposed fuzzy logic control scheme while NOx and soot emissions have been significantly reduced by 34% and 82%, respectively.

Real-time fuzzy logic controllers (RFLC) have been developed for the VGT and EGR control on a heavy-duty diesel engine. Previous studies show that compared to the VGT and EGR controlled by conventional PID controllers, there is a increase of engine torque and a reduction of engine emissions when the engine is running on the same condition. This work carried out robustness evaluation of the RFLC control using the 1D transient engine model built in AVL-BOOST simulation platform. The evaluation includes a sudden air leak test and a turbocharger mechanical efficiency deterioration test. Simulation results show that the fuzzy logic controller is able to make necessary adjustments in both tests. It is able to compensate for the inlet pressure and flow loss either due to the air leak or the efficiency drop without losing engine torque and producing excessive increase of the soot and NOx.

As their high specific power and long cycle life over conventional batteries, Ultracapacitors have been thought as a good alternative/supplement for energy storage for city buses which operate considerable fast acceleration, deceleration and stop. In the current study, the powertrain system for a PEV (Pure Electric Vehicle) bus with batteries and ultra-capacitors for energy storage were developed. While high vehicle performance and low systemic cost were considered as main factors for the system configuration, different designs for the combination between batteries and ultra-capacitors were proposed and investigated. Based on optimized control strategies for energy management with and without stop-charging, the system performance was numerically simulated with Matlab/Simulink and ADVISOR under the UK bus driving cycle. The results show the involvement of Ultracapacitors can improve the performance of the vehicle and also reduce the cost. When stop-charging is employed, the battery pack can be completely removed and the Ultracapacitor can provide all the electric energy required by the bus.

The oil distribution system of an automotive light duty engine typically has an oil pump mechanically driven through the front-endancillaries-drive or directly off the crankshaft. Delivery pressure is regulated by a relief valve to provide an oil gallery pressure of typically 3 to 4 bar absolute at fully-warm engine running conditions. Electrification of the oil pump drive is one way to decouple pump delivery from engine speed, but this does not alter the flow distribution between parts of the engine requiring lubrication. Here, the behaviour and benefits of a system with an electrically driven, fixed displacement pump and a distributor providing control over flow to crankshaft main bearings and big end bearings is examined. The aim has been to demonstrate that by controlling flow to these bearings, without changing flow to other parts of the engine, significant reductions in engine friction can be achieved. The study has been conducted on a 1.5litre, 4 cylinder turbocharged diesel engine. By reducing the feed pressure to the bearings from a baseline pressure of 3bar absolute to 1.5 bar absolute, reductions in engine rubbing friction mean effective pressure of up to 14% has been achieved at light load. Similar reductions in friction were recorded across a speed range of 1000-2000 rev/min and net indicated mean effective pressures up to 3.5 bar. The ranges were conservatively limited to protect against bearing damage. The paper reports details of the oil system modifications and the test results. The fuel economy benefit due solely to the friction reduction, not including any benefit from a reduction in oil pump work, is around 1½ % over the New European Drive Cycle (NEDC). The reduction in friction is demonstrably significant and represents an area with great potential to improve engine efficiency.

Abstract— In this paper, we propose a Control Lyapunov
Function based nonlinear robust controller for turbocharged biodiesel engine. A model-based approach has been used which predicts experimentally observed engine performance for biodiesel. The basic idea is to develop inverse optimal control and utilize Lyapunov function in order to achieve good performance. The obtained controller gain guarantees the global convergence of the system and regulates the flows for the Variable Geometry Turbocharger and Exhaust Gas Recirculation systems in order to minimize the NOx emission and smoke of biodiesel engine. Simulation of the control performance shows the effectiveness of this approach.

This work addresses the issues of actuator fault detection and isolation for diesel engines. We are particularly interested in faults affecting the exhaust gas recirculation (EGR) and the variable geometry turbocharger (VGT) actuator valves. A bank of observer-based residuals is designed using a nonlinear mean value model of diesel engines. Each residual on the proposed scheme is based on a nonlinear unknown input observer and designed to be insensitive to only one fault. By using this scheme, each actuator fault can be easily isolated since only one residual goes to zero while the others do not. A decision algorithm based on multi-CUSUM is used. The performances of the proposed approach are shown through a real application to a Caterpillar 3126b engine.

With a view to understanding the air-fuel mixing behavior and the effects of the mixture quality on the emissions formation and engine performance, a new quantitative factor of the in-cylinder air-fuel homogeneity named Homogeneity Factor (HF) has been developed. Its characteristics under various injection conditions and air swirl motions within the cylinder have been investigated with CFD simulation. The results have shown that air-fuel homogeneity is essentially affected by the spatial and temporal fuel distribution within the combustion chamber. Higher injection pressure, longer dwell time and increased pilot fuel quantities can contribute to better mixing quality resulting in increased HF and optimum engine performance with low fuel consumption and soot emissions. With regard to the in-cylinder air motion, increasing swirl ratio enhances the air-fuel mixing quality which has been reflected in the variation of the HF. As a result, increased in-cylinder pressure and temperature caused by the optimized air-fuel mixing improved the combustion efficiency.

An ANFIS (Adaptive neuro-fuzzy inference system) controller which bases on Takagi-Sugeno’s method and combines the advantages of neural controller and fuzzy multi-variable controller has been studied and developed for the real-time control of EGR and VGT in a diesel
engine. In the AVL-BOOST and Matlab/Simulink co-simulation environment, the control performance of ANFIS controller has been compared with those optimal control strategies based on a fuzzy logic controller. Results show the new controller can have more active control to EGR position and the optimal emission levels can be maintained.

Due to the inherent nonlinearity of the diesel engine, real-time control of the variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) valve still remains a challenging task. A controller has to be capable of coping with the transient operating condition of the engine, the interactions between the VGT and EGR, and also the trade-off effect in this control problem. In this work, novel real-time fuzzy logic controllers (RFLC) were developed and tested. Firstly, the proposed controllers were calibrated and validated in a transient diesel engine model which was developed and validated against the Caterpillar 3126B engine test bed located at the University of Sussex. The controllers were then further tested on the engine test bed. Compared to conventional controllers, the proposed controllers can effectively reduce engine emissions as well as fuel consumption. Experimental results show that compared to the baseline engine running on the Nonroad Transient Cycle (NRTC), mean values of the exhaust gas opacity and the nitrogen oxides (NOx) emission production were reduced by 36.8% and 33%, respectively. Instant specific fuel consumption of the RFLC engine was also reduced by up to 50% compared to the baseline engine during the test. Moreover, the proposed fuzzy logic controllers can also reduce development time and cost by avoiding extensive engine mapping of inlet air pressure and flow. When on-line emission measurements were not available, on-board emission predictors were developed and tested to supply the proposed fuzzy logic controller with predictions of soot and NOx production. Alternatively, adaptive neuro fuzzy inference system (ANFIS) controllers, which can learn from fuzzy logic controllers, were developed and tested. In the end, the proposed fuzzy logic controllers were compared with PI controllers using the transient engine model.