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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.

A control strategy has been designed for a city bus equipped with a pneumatic hybrid propulsion system. The control system design is based on the precise management of energy flows during both energy storage and regeneration. Energy recovered from the braking process is stored in the form of compressed air that is redeployed for engine start and to supplement the engine air supply during vehicle acceleration. Operation modes are changed dynamically and the energy distribution is controlled to realize three principal functions: Stop-Start, Boost and Regenerative Braking. A forward facing simulation model facilitates an analysis of the vehicle dynamic performance, engine transient response, fuel economy and energy usage.

One of the most critical challenges currently facing the diesel engine industry is how to improve fuel economy under emission regulations. Improvement in fuel economy can be achieved by precisely controlling Air/Fuel ratio and by monitoring fuel consumption in real time. Accurate and repeatable measurements of fuel rate play a critical role in successfully controlling air/fuel ratio and in monitoring fuel consumption. Volumetric and gravimetric measurements are well-known methods for measuring fuel consumption of internal combustion engines. However, these methods are not suitable for obtaining fuel flow rate data used in real-time control/measurement. In this paper, neural networks are used to solve the problem concerning discontinuous data of fuel flow rate measured by using an AVL 733 s fuel meter. The continuous parts of discontinuous fuel flow rate are used to train and validate a neural network, which can then be used to predict the discontinuous parts of the fuel flow rate.

Measurement accuracy and repeatability for fuel rate is the key to successfully improve fuel economy of diesel engines as fuel economy could only be achieve by precisely controlling air/fuel ratio and monitor real-time fuel consumption. The volumetric and gravimetric measurement principles are well-known methods to measure the fuel consumption of internal combustion engines. However, the fuel flow rate measured by these methods is not suitable for either real-time control or real-time measurement purposes. The problem concerning discontinuous data of fuel flow rate measured by using an AVL 733s fuel meter was solved for the steady state scenario by using neural networks. It is easier to choose inputs of the neural networks for the steady state scenario because the inputs could be chosen as the particular inputs which excited the system in the application.

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 hybrid electric vehicle (HEV) is already available commercially and is demonstrating the very significant benefit of improved fuel consumption. The costs associated with the hybrid vehicle are still high, and for novel types of auxiliary power unit are still undefined. Measures to improve the performance of HEV technology are emerging and include the traffic and navigation information which forms part of the telematics infrastructure. One of the key issues in enhancing HEV performance is journey prediction. Journey time and energy requirements can be products of a telematics system but form the basis for a significant performance enhancement to an HEV.

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.

This paper presents a control system design strategy for a novel fuel cell - internal combustion engine hybrid power system. Dynamic control oriented models of the system components are developed. The transient behavior of the system components is investigated in order to determine control parameters and set-points. The analysis presented here is the first step towards development of a controller for this complex system. The results indicate various possibilities for control design and development. A control strategy is discussed to achieve system performance optimization.

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.

The pursuit of improved fuel economy is becoming an increasingly important objective for automotive manufacturers. The field of thermo-electrics is highlighted as a promising technology. The figure of merit, Z is the primary measure of the effectiveness of a thermo-electric material, and the values now being offered by researchers have reached the level where new applications become attractive. It is feasible to consider such modules incorporated into a thermoelectric generator to recover waste heat from exhaust gas flow – an available energy stream that has traditionally been neglected as unusable. As a precursor to a costly experimental study it is desirable to accurately simulate the application of a thermo-electric system to a vehicle exhaust to understand both the feasibility and potential drawbacks.

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.

In modern production diesel engine control systems, fuel path control is still largely conducted through a system of tables that set mode, timing and injection quantity and with common rail systems, rail pressure. In the hands of an experienced team, such systems have proved so far able to meet emissions standards, but they lack the analytical underpinning that lead to systematic solutions. In high degree of freedom systems typified by modern fuel injection, there is substantial scope to deploy optimising closed loop strategies during calibration and potentially in the delivered product. In an optimising controller, a digital algorithm will explicitly trade-off conflicting objectives and follow trajectories during transients that continue to meet a defined set of criteria. Such an optimising controller must be based on a model of the system behaviour which is used in real time to investigate the consequences of proposed control actions.

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.

Constraints change as pollutant standards or embedded diagnosis demands require improvements in model accuracy and their suitability for control algorithm synthesis. From thermodynamic mathematical modelling to non-parametric models, a wide range of techniques has been investigated for the last thirty years involving both physicists and control engineers. The purpose of this paper is to give an overview of current modelling techniques oriented control analysis and design for compression ignition engines. Short examples illustrate each techniques and existing applications are considered. Comparison of various engine models exhibit the trend to include more physical knowledge inside model-based control design.

The aim of this paper is to compile the state of the art of engine control and develop scenarios for improvements in a number of applications of engine control where the pace of technology change is at its most marked. The first application is control of downsized engines with enhancement of combustion using direct injection, variable valve actuation and turbo charging. The second application is electrification of the powertrain with its impact on engine control. Various architectures are explored such as micro, mild, full hybrid and range extenders. The third application is exhaust gas after-treatment, with a focus on the trade-off between engine and after-treatment control. The fourth application is implementation of powertrain control systems, hardware, software, methods, and tools. The paper summarizes several examples where the performance depends on the availability of control systems for automotive applications.

Thermoelectric generator (TEG) has received more and more attention in its application in the harvesting of waste thermal energy in automotive engines. Even though the commercial Bismuth Telluride thermoelectric material only have 5% efficiency and 250°C hot side temperature limit, it is possible to generate peak 1kW electrical energy from a heavy-duty engine. If being equipped with 500W TEG, a passenger car has potential to save more than 2% fuel consumption and hence CO2 emission reduction. TEG has advantages of compact and motionless parts over other thermal harvest technologies such as Organic Rankine Cycle (ORC) and Turbo-Compound (TC). Intense research works are being carried on improving the thermal efficiency of the thermoelectric materials and increasing the hot side temperature limit. Future thermoelectric modules are expected to have 10% to 20% efficiency and over 500°C hot side temperature limit.

The TC48 project is developing a state-of-the-art, exceptionally low cost, 48V Plug-in hybrid electric (PHEV) demonstration drivetrain suitable for electrically powered urban driving, hybrid operation, and internal combustion engine powered high speed motoring. This paper explains the motivation for the project, and presents the layout options considered and the rationale by which these were reduced. The vehicle simulation model used to evaluate the layout options is described and discussed. The modelling work was used in order to support and justify the design choices made. The design of the vehicle's control systems is discussed, presenting simulation results. The physical embodiment of the design is not reported in this paper. The paper describes analysis of small vehicles in the marketplace, including aspects of range and cost, leading to the justification for the specification of the TC48 system.

Since the first stop-start system introduced in 1983, more and more vehicles have been equipped with this kind of automatic engine control system. Recently, it was found that there is strong correlation between engine resting position and the subsequent engine start time. The utilization of the synchronization time working from a required engine stop position prior the engine start request was shown to reduce start times. Hence the position control of an engine during shutdown becomes more significant. A naturally aspirated engine was modelled using the GT-Suite modelling environment to facilitate the development of position controllers using Simulink ®. The use of respectively the throttle and a belt mounted motor generator to provide a control input was considered. Proportional-Integral-Differential (PID), sliding mode and deadbeat control strategies were each used in this study.

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.