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For the vehicles with frequent stop-start operations, fuel consumption can be reduced significantly by implementing stop-start operation. As one way to realize this goal, the pneumatic hybrid technology converts kinetic energy to pneumatic energy by compressing air into air tanks installed on the vehicle. The compressed air can then be reused to drive an air starter to realize a regenerative stop-start function. Furthermore, the pneumatic hybrid can eliminate turbo-lag by injecting compressed air into manifold and a correspondingly larger amount of fuel into the cylinder to build-up full-load torque almost immediately. This paper takes the pneumatic hybrid engine as the research object, focusing on evaluating the improvement of fuel economy of multiple air tanks in different test cycles. Also theoretical analysis the benefits of extra boost on reducing turbo-lag to achieve better performance.

This paper presents the implementation of a vehicle and powertrain model of the parallel hybrid electric vehicle which can be used for several purposes: as a model for estimating fuel consumption, as a model for estimating performance, and as a control model for the hybrid powertrain optimisation. The model is specified as a multi-domain physical model in MATLAB Simscape, which captures the key electrical, mechanical and thermal energy flows in the vehicles. By applying hand crafted boundary conditions, this model can be simulated either in the forwards or backwards direction, and it can easily be simplified as required to address specific control problems. Modelling in the forwards direction, the driver inputs are specified, and the vehicle response is the model output. In the backwards direction, the vehicle velocity as a function of time is the specified input, and the engine torque, and fuel consumption are the model outputs.

Thermoelectric generator has very quickly become a hot research topic in the last five years because its broad application area and very attractive features such as no moving parts, low maintenance, variety of thermoelectric materials that total together cover a wide temperature range. The biggest disadvantage of the thermoelectric generator is its low conversion efficiency. So that when design and manufacture a thermoelectric generator for exhaust waste heat recovery from an automotive engine, the benefit of fuel consumption from applying a thermoelectric generator would be very sensitive to the weight, the dimensions, the cost and the practical conversion efficiency. Additionally, the exhaust gas conditions vary with the change of engine operating point. This creates a big challenge for the design of the hot side heat exchanger in terms of optimizing the electrical output of the thermoelectric generator during an engine transient cycle.

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 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.

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.

Recovering the braking energy and reusing it can significantly improve the fuel economy of a vehicle which is subject to frequent braking events such as a city bus. As one way to achieve this goal, pneumatic hybrid technology converts kinetic energy to pneumatic energy by compressing air into tanks during braking, and then reuses the compressed air to power an air starter to realize a regenerative Stop-Start function. Unlike the pure electric or hybrid electric passenger car, the pneumatic hybrid city bus uses the rear axle to achieve regenerative braking function. In this paper we discuss research into the blending of pneumatic regenerative braking and mechanical frictional braking at the rear axle. The aim of the braking function is to recover as much energy as possible and at the same time distribute the total braking effort between the front and rear axles to achieve stable braking performance.

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 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.

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).

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.

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.

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.

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 pursuit of fuel economy is forcing technology change across the range of control and engine management technologies. Improved thermal management has been addressed in order to promote fast warm-up, improved exhaust gas after-treatment performance, and lower variance in combustion through a consistent and high cylinder head temperature. Temperature management of exhaust gas is of increasing interest because of the need to maintain efficiency in after-treatment devices. More effective temperature management places requirements on heat exchange systems, and offers the potential for bottoming and heat recovery cycles that use energy transferred from the exhaust stream. Turbo-compounding is already established in heavy duty engines, where a reduction in exhaust gas temperature is the consequence of an additional stage of expansion through an exhaust turbine. A new project in electric turbo-compounding offers flexibility in the control of energy extracted from the exhaust stream[1].

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.

Diesel homogeneous charge compression ignition (HCCI) engines with early injection can result in significant spray/wall impingement which seriously affects the fuel efficiency and emissions. In this paper, the spray/wall interaction models which are available in the literatures are reviewed, and the characteristics of modeling including spray impingement regime, splash threshold, mass fraction, size and velocity of the second droplets are summarized. Then three well developed spray/wall interaction models, O'Rourke and Amsden (OA) model, Bai and Gosman (BG) model and Han, Xu and Trigui (HXT) model, are implemented into KIVA-3V code, and validated by the experimental data from recent literatures under the conditions related to diesel HCCI engines. By comparing the spray pattern, droplet mass, size and velocity after the impingement, the thickness of the wall film and vapor distribution with the experimental data, the performance of these three models are evaluated.

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.

When a diesel engine is running at steady state, the diesel combustion process still has some level of variation from cycle to cycle, even if engine load and all control inputs are fixed. This variation is a disturbance for the speed governor, and it could lead to less than optimal engine performance in terms of fuel economy, exhaust gas emission and noise emission. The most effective way to reduce this steady state combustion variation is by applying fuel path feedback control. The control action can be performed at a fixed frequency, or at a defined cycle event time. Intra-cycle control has the highest capacity to suppress the combustion deviation, as it measures the current cycle combustion performance and compensates for it within the same cycle using a very fast control response. Correct knowledge and a model of the disturbance sources and combustion variation patterns are essential in the design process of this intra-cycle control strategy.

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.