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The performance of energy flow management strategies is essential for the success of hybrid electric vehicles (HEVs), which are considered amongst the most promising solutions for improving fuel economy as well as reducing exhaust emissions. The heavy duty HEVs engaged in cycles characterized by start-stop configuration has attracted widely interests, especially in off-road applications. In this paper, a fuzzy equivalent consumption minimization strategy (F-ECMS) is proposed as an intelligent real-time energy management solution for heavy duty HEVs. The online optimization problem is formulated as minimizing a cost function, in terms of weighted fuel power and electrical power. A fuzzy rule-based approach is applied on the weight tuning within the cost function, with respect to the variations of the battery state-of-charge (SOC) and elapsed time.

In this paper, a robust adaptive optimal tracking control design for the air-path system of diesel engines with uncertain parameters and external driver commands is proposed. First, an optimal controller based on the analytic solution of a performance index is derived. It achieves tracking of suitable references (corresponding to low emissions and fuel consumption) for both the air-fuel ratio and the fraction of the recirculated exhaust gas. Then, a fuzzy estimation algorithm is used to identify the plant parameters and consequently to adapt the controller online. The simulated diesel engine is a medium duty Caterpillar 3126B with six cylinders, equipped with a variable geometry turbocharger and an exhaust gas recirculation valve. The proposed controller design is based on the reduced third order mean value model and implemented as a closed-form nonlinear model predictive control law on the full order model.

The two-stage turbocharging technique is an effective way to improve performance and reduce emissions in diesel engines. In this paper, we consider a diesel engine equipped with an exhaust gas recirculation (EGR) valve and two turbochargers in series. The low pressure turbine is of fixed geometry and the high pressure turbine is a variable geometry turbine (VGT). The control objective is to regulate air-to-fuel (AFR), EGR exhaust fraction and the power ratio of the two turbines by coordinated manipulation of the EGR and VGT actuators. Unlike engines with a single turbocharger, in two-staged turbocharged engines, regulation of the power ratio of the turbines is also needed in order to adequately define the equilibrium point of the engine airpath. First, a mean value engine model (MVEM) is proposed to physically describe the air path dynamics. With rich excitation of the controls in the MVEM, we identify several linear models for different areas of the engine speed-torque envelope.

Traditionally, university research in engine technology has been focused on fundamental engine phenomena. Increasingly however, research topics are developing in the form of systems issues. Examples include air and exhaust gas recirculation (EGR) management, after-treatment systems, engine cooling, hybrid systems and energy recovery. This trend leads to the need for engine research to be conducted using currently available products and components that are re-configured or incrementally improved to support a particular research investigation. A production engine will include an electronic control unit (ECU) that must be understood and utilised or simply removed and circumvented. In general the intellectual property (IP) limitations places on ECUs by their suppliers mean that they cannot be used. The supplier of the ECU is usually unable to reveal any detail of the implementation. As a consequence any research using production hardware is seriously disadvantaged from the beginning.

Variable valve actuation in heavy duty diesel engines is not well documented, because of diesel engine feature, such as, unthrottled air handling, which gives little room to improve pumping loss; a very high compression ratio, which makes the clearance between the piston and valve small at the top dead center. In order to avoid strike the piston while maximizing the valve movement scope, different strategies are adopted in this paper: (1) While exhaust valve closing is fixed, exhaust valve opening is changed; (2) While exhaust valve closing is fixed, late exhaust valve opening: (3) While inlet valve opening is fixed, inlet valve closing is changed; (4) Delayed Inlet valve and exhaust valve openings and closings; (5) Changing exhaust valve timing; (6) changing inlet valve timing; (7) Changing both inlet and exhaust timing, will be used.

This work describes the application of Non-Linear Autoregressive Models with Exogenous Inputs (NLARX) in order to predict the NOx emissions of heavy-duty diesel engines. Two experiments are presented: 1.) a Non-Road-Transient-Cycle (NRTC) 2.) a composition of different engine operation modes and different engine calibrations. Data sets are pre-processed by normalization and re-arranged into training and validation sets. The chosen model is taken from the MATLAB Neural Network Toolbox using the algorithms provided. It is teacher forced trained and then validated. Training results show recognizable performance. However, the validation shows the potential of the chosen method.

Variable compression ratio in conjunction with a control system is an effective way to improve performance and reduce emissions in a diesel engine. There are various methods that may be employed that include geometry changes and varying valve timing to change the effective compression ratio. In this paper, a simulation study is presented that is based on a modern, multi-cylinder, fixed compression ratio diesel engine equipped with exhaust gas recirculation (EGR) and a variable geometry turbocharger (VGT). The engine is represented using the GT-Power code, and includes a predictive combustion model. The aim of the investigation is to identify the impact of variable compression ratio on fuel economy and emission reduction and whether realistic optimal conditions exist. This paper describes how a formal design of experiments procedure is used to define the simulation conditions. Cost functions are defined with different weights for fuel consumption, NOx and soot emissions.

Modeling is of increasing significance to the automotive applications of catalyst systems. For exhaust gas after-treatment, prediction of exhaust emissions plays an important role in the design process for new vehicles. However both control and diagnosis requirements on the vehicle have created the need for control-oriented models. A control-oriented model is both compact and accurate and may be embedded in a computer system as a component of a real-time algorithm. Modeling of catalysts can take place at a molecular level where computational techniques are only just emerging. Detailed kinetics modeling done alongside thermal and fluid modeling of the catalyst yields important details about the dynamic behavior of the catalyst system. Approaches to developing control-oriented model have tended to use the simplest statements of kinetics. In general, the development of such models requires the inclusion of some chemical kinetics.

Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as the promising solution in engine downsizing. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The electrified turbocharger consists of a variable geometry turbocharger (VGT) and an electric motor (EM) within the turbocharger bearing housing, where the EM is capable in bi-directional power transfer. The VGT, EM, and exhaust gas recirculation (EGR) valve all impact the dynamics of air path. In this paper, the dynamics in an electrified turbocharged diesel engine (ETDE), especially the couplings between different loops in the air path is analyzed. Furthermore, an explicit principle in selecting control variables is proposed. Based on the analysis, a model-based multi-input multi-output (MIMO) decoupling controller is designed to regulate the air path dynamics.

The injection timing of a Diesel internal combustion engine typically follows a prescribed sequence depending on the operating condition using open loop control. Due to advances in sensors and digital electronics it is now possible to implement closed loop control based on in cylinder pressure values. Typically this control action is slow, and it may take several cycles or at least one cycle (cycle-to-cycle control). Using high speed sensors, it becomes technically possible to measure pressure deviations and correct them within the same cycle (intra-cycle control). For example the in cylinder pressure after the pilot inject can be measured, and the timing of the main injection can be adjusted in timing and duration to compensate any deviations in pressure from the expected reference value. This level of control can significantly reduce the deviations between cycles and cylinders, and it can also improve the transient behavior of the engine.

For diesel engines, fuel path control plays a key role in achieving optimal emissions and fuel economy performance. There are several fuel path parameters that strongly affect the engine performance by changing the combustion process, by modifying for example, start of injection and fuel rail pressure. This is a multi-input multi-output problem. Linear Model Predictive Control (MPC) is a good approach for such a system with optimal solution. However, fuel path has fast dynamics. On-line optimisation MPC is not the good choice to cope with such fast dynamics. Explicit MPC uses off-line optimisation, therefore, it can be used to control the system with fast dynamics.

Most modern diesel engines are equipped with common fuel rail system. The common fuel rail pressure and start of injection are two important fuel path control variables which are needed to be carefully calibrated over all engine operation range. They both have big effects on engine emissions, fuel consumptions and combustion noise performance. Though there are mature techniques such as design of experiment, model based calibration together with optimization method for engine calibration task, the engine test points are still many and the calibration costs are still high. Besides, the outputs of the calibration are look up tables or maps which are used in engine open loop control strategy in engine control system. Open loop control system has no adaptive and disturbance rejection ability. So the initially optimally calibrated look up control tables will gradually become less and less optimal when the engine is aging.

The use of thermo-electric (TE) generation systems in internal combustion engines (ICEs) to reduce the carbon dioxide emission by harnessing the exhaust thermal energy is showing increasing promise. In addition, integration with after treatment devices is a development route for this technology that offers a great potential. Recent work on TE systems have shown that the overall efficiency of present TE generation systems are constrained by, the limitations of the conversion efficiency and operating temperatures of TE materials; fabrication quality, durability and thermal performance of the thermo-electric modules (TEMs); geometrical configuration and heat exchange efficiency of thermo-electric generator (TEG) and; conversion techniques of the TEG's electrical output to a form suitable for vehicle systems.

The process of controlling tailpipe emissions leads to the need to understand the dynamic behaviour of the after-treatment devices. The model provides the basis for design prediction, on-line diagnosis and real time control. Although a number of models have been presented in the literature, their efficient performance continues to require further development and validation to meet increasingly demanding requirements. Models have been developed that use the basic physical framework including thermal behaviour, fluid mechanics and basic chemistries. As more demands are placed on models, more phenomena need to be taken into account and in particular, progressively more of the chemistry of the Three-Way Catalyst (TWC) itself. In this paper we present a black-box model for a three-way catalytic converter that has been developed and tested using real experimental data.

Two identical commercial Thermo-Electric Modules (TEMs) were assembled on a plate type heat exchanger to form a Thermoelectric Generator (TEG) unit in this study. This unit was tested on the Exhaust Gas Recirculation (EGR) flow path of a test engine. The data collected from the test was used to develop and validate a steady state, zero dimensional numerical model of the TEG. Using this model and the EGR path flow conditions from a 30% torque Non-Road Transient Cycle (NRTC) engine test, an optimization of the number of TEM units in this TEG device was conducted. The reduction in fuel consumption during the transient test cycle was estimated based on the engine instantaneous Brake Specific Fuel Consumption (BSFC). The perfect conversion of TEG recovered electrical energy to engine shaft mechanical energy was assumed. Simulations were performed for a single TEG unit (i.e. 2 TEMs) to up to 50 TEG units (i.e. 100 TEMs).

An automotive engine can be more efficient if thermoelectric generators (TEG) are used to convert a portion of the exhaust gas enthalpy into electricity. Due to the relatively low cost of the incoming thermal energy, the efficiency of the TEG is not an overriding consideration. Instead, the maximum power output (MPO) is the first priority. The MPO of the TEG is closely related to not only the thermoelectric materials properties, but also the operating conditions. This study shows the development of a numerical TEG model integrated with a plate-fin heat exchanger, which is designed for automotive waste heat recovery (WHR) in the exhaust gas recirculation (EGR) path in a diesel engine. This model takes into account the following factors: the exhaust gas properties’ variation along the flow direction, temperature influence on the thermoelectric materials, thermal contact effect, and heat transfer leakage effect. Its accuracy has been checked using engine test data.

The intrinsic model accuracy limit of a commonly used Exhaust Gas Recirculation (EGR) mass flow rate model in diesel engine air path control is discussed in this paper. This EGR mass flow rate model is based on the flow of a compressible ideal gas with unchanged specific heat ratio through a restriction cross-area within a duct. A practical identification procedure of the model parameters is proposed based on the analysis of the engine data and model structure. This procedure has several advantages which include simplicity, low computation burden and low engine test cost. It is shown that model tuning requires only an EGR valve sweep test at a few engine steady state operating points.