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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.

Fuel cell hybrid systems have emerged rapidly in efforts to reduce emissions. The success of these systems mainly depends on implementation of suitable control architectures. This paper presents a control system design for a novel fuel cell - IC Engine hybrid power system. Control oriented models of the system components are developed and integrated. Based on the simulation results of the system model, the control variables are identified. The main objective for the control design is to manage fuel, air and exhaust flows in a way to deliver the required load on the system within local constraints. The controller developed for regulating flows in the system is based on model predictive control theory. The performance of the overall control system is assessed through simulations on a nonlinear dynamic model.

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.

The idea of thermal energy recovery from vehicle engine exhaust flow is now well supported and funded. Through a number of research projects, several component technologies have been identified. Rankine cycle, turbo-compounding and thermo-electric systems have all attracted interest. Fuel economy improvements vary depending on the drive cycle and the capability of the underlying technologies, but have been reported as high as 25%. Our work at Sussex on a form of Rankine cycle has revealed generic issues about the control of thermal recovery and the associated modelling requirements. Typical issues include the balancing the rate of heat input to the recovery system with the loss of useful work from large temperature differences. The size of components dictates the control authority over the system and consequently its ability to follow changing conditions.

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.

Energy recovery from IC engines has proved to be of considerable interest across the range of vehicle applications. The motivation is substantial fuel economy gain that can be achieved with a minimal affect on the “host” technology of the vehicle. This paper reviews the initial results of a research project whose objective has been to identify system concepts and control methods for thermal recovery techniques. A vapour power cycle is the means of energy transfer. The architecture of the system is considered along with support of the fuel economy claims with the results of some hybrid vehicle modelling. An overview of the latest experimental equipment and design of the heat exchanger is presented. The choice of control architecture and strategy, whose goal is overall efficiency of the engine system, is presented and discussed. Some initial control results are presented.

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.

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.

This paper reports on an investigation into the potential for a thermoelectric generator (TEG) to improve the fuel economy of a mild hybrid vehicle. A simulation model of a parallel hybrid vehicle equipped with a TEG in the exhaust system is presented. This model is made up by three sub-models: a parallel hybrid vehicle model, an exhaust model and a TEG model. The model is based on a quasi-static approach, which runs a fast and simple estimation of the fuel consumption and CO2 emissions. The model is validated against both experimental and published data. Using this model, the annual fuel saving, CO2 reduction and net present value (NPV) of the TEG’s life time fuel saving are all investigated. The model is also used as a flexible tool for analysis of the sensitivity of vehicle fuel consumption to the TEG design parameters. The analysis results give an effective basis for optimization of the TEG design.

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.

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.

More and more stringent emission regulations require advanced control technologies for combustion engines. This goes along with increased monitoring requirements of engine behaviour. In case of emissions behaviour and fuel consumption the actual combustion efficiency is of highest interest. A key parameter of combustion conditions is the in-cylinder pressure during engine cycle. The measurement and detection is difficult and cost intensive. Hence, modelling of in-cylinder conditions is a promising approach for finding optimum control behaviour. However, on-line controller design requires real-time scenarios which are difficult to model and current modelling approaches are either time consuming or inaccurate. This paper presents a new approach of in-cylinder condition prediction. Rather than reconstructing in-cylinder pressure signals from vibration transferred signals through cylinder heads or rods this approach predicts the conditions.

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.