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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.

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.

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.

Market trends for increased engine power and more electrical energy on the powergrid (3kW+), along with customer demands for fuel consumption improvements and emissions reduction, are driving requirements for component electrification, including turbochargers. GTDI engines waste significant exhaust enthalpy; even at moderate loads the WG (Wastegate) starts to open to regulate the turbine power. This action is required to reduce EBP (Exhaust Back Pressure). Another factor is catalyst protection, where the emissions device is placed downstream turbine. Lambda enrichment or over-fueling is used to perform this. However, the turbine has a temperature drop across it when used for energy recovery. Since catalyst performance is critical for emissions, the only reasonable location for an additional device is downstream of it. This is a challenge for any additional energy recovery, but a smaller turbine is a design requirement, optimized to operate at lower pressure ratios.

The importance of new technologies to improve the performance and fuel economy of internal combustion engines is now widely recognized and is essential to achieve CO₂ emissions targets and energy security. Increased hybridization, combustion improvements, friction reduction and ancillary developments are all playing an important part in achieving these goals. Turbocharging technology is established in the diesel engine field and will become more prominent as gasoline engine downsizing is more widely introduced to achieve significant fuel economy improvements. The work presented here introduces, for the first time, a new technology that applies conventional turbomachinery hardware to depressurize the exhaust system of almost any internal combustion engine by novel routing of the exhaust gases. The exhaust stroke of the piston is exposed to this low pressure leading to reduced or even reversed pumping losses, offering ≻5% increased engine torque and up to 5% reduced fuel consumption.

Significant exhaust enthalpy is wasted in gasoline turbocharged direct injection (GTDI) engines; even at moderate loads the WG (Wastegate) starts to open. This action is required to reduce EBP (Exhaust Back Pressure). Another factor is catalyst protection, placed downstream turbine. Lambda enrichment is used to perform this. However, the conventional turbine has a temperature drop across it when used for energy recovery. Catalyst performance is critical for emissions, therefore the only location for any additional device is downstream of it. This is a challenge for any additional energy recovery, but a smaller turbine is a design requirement, optimised to work at lower operating pressure ratios. A WAVE model of the 2.0L GTDI engine was adapted to include a TG (Turbogenerator) and TBV (Turbine Bypass Valve) with the TG in a mechanical turbocompounding configuration, calibrated with steady state dynamometer data to estimate drive cycle benefit.

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.

Steady state engine dynamometer testing provides the highest level of detail for understanding fundamental engine combustion. It can provide insight into pollutant formation mechanisms and methods for minimizing fuel consumption. However, steady-state dynamometer tests are normally carried out at test conditions far removed from the actual conditions that a vehicle engine encounters. This paper describes the application of a simple powertrain model to define steady-state engine test conditions that are more representative of real-world engine operation. The model uses a backward-facing, modular structure. The model is validated against two powertrain configurations: a conventional powertrain equipped with a continuously variable transmission (CVT) and a parallel hybrid powertrain. Powertrain parameters and performance data for validation for both cases are supplied from the literature. The model is shown to agree well with both sets of published experimental results.

The Swedish Biomimetics 3000's μMist® platform technology has been used to develop a radically new injection system. This prototype system, developed and characterized with support from Lotus, as part of Swedish Biomimetics 3000®'s V₂IO innovation accelerating model, delivers improved combustion efficiency through achieving exceptionally small droplets, at fuel rail pressures far less than conventional GDI systems and as low as PFI systems. The system gives the opportunity to prepare and deliver all of the fuel load for the engine while the intake valves are open and after the exhaust valves have closed, thereby offering the potential to use advanced charge scavenging techniques in PFI engines which have hitherto been restricted to direct-injection engines, and at a lower system cost than a GDI injection system.