Search Results

Considerable efforts have been made in the automotive industry on powertrains in order to minimize the energy required by passenger cars. This can be done by improving factors such as the technologies used and the way the energy is used.Losses can be recovered from thermal irreversible power sources. The lost energy contained in the exhaust gases and the coolant can be recovered using two Rankine Machines. As Rankine Cycles work better on a stabilized operating point, a Series Hybrid Electric Vehicle (SHEV) would appear to have a great potential for this technology. The two Rankine machines can be chained: the high temperature machine recovers the lost exhaust gases energy, while the low temperature machine recovers both the lost energy coming from the coolant plus the energy coming from the low temperature side of the previous machine.

Increasing the degrees of freedom in the air path has become a popular way to reduce the fuel consumption and pollutant emissions of modern combustion engines. That is why technical definitions will usually contain components such as multi or single-stage turbocharger, throttle, exhaust gas recirculation loops, wastegate, variable valve timing or phasing, etc. One of the biggest challenges is to precisely quantify the gas flows through the engine. They include fresh and burnt gases, with trapping and scavenging phenomena. An accurate prediction of these values leads to an efficient control of the engine air fuel ratio and torque. Fuel consumption and pollutant emissions are then minimized. In this paper, we propose to use an artificial neural network- based model as a prediction tool for the engine volumetric efficiency. Results are presented for a downsized turbocharged spark-ignited engine, equipped with inlet and outlet variable valve timing.

In Hybrid Electric Vehicles (HEV), the electrical hybridization offers different ways to reduce the fuel consumption: kinetic energy recuperation during vehicle deceleration, possibility of stopping the engine, and intelligent Energy Management System (EMS). Besides, with the future more stringent standards, there is a need to integrate the pollutant emissions in the EMS, since strictly reducing the fuel consumption can increase the emissions. The paper presents an optimal energy management strategy with constraints on pollutant emissions for gasoline-HEV, taking into account the 3-Way Catalyst Converter (3WCC). Based on a complete model of the powertrain, a mixed fuel consumption / pollutant emissions performance index is minimized with the Pontryaguin Minimum Principle (PMP) and two states, the battery State Of Charge and the 3WCC temperature.

In the past few years, the increasing market penetration of downsized engines has reduced the pollutant emissions of internal combustion engines. The addition of a turbocharger to the air path has usually enabled the dynamic performances of the vehicles to be maintained. However, in the development process, deciding on the appropriate set of components is not straightforward and a lengthy fitting process is usually required to find the right turbocharger. Car manufacturers usually have access to a limited library of compressors and turbines which have actually been built and for which measurement campaigns have been carried out. This study is motivated by the need to extend the libraries available for simulation in order to provide a substantial increase in freedom in the matching process.

Data maps are easy to put in place and require very low calculation time. As a consequence they are often valued over fully physic-based models. This is particularly true when it is question of turbochargers. However, even if these maps are directly provided by the manufacturer, they usually do not cover the entire engine operating range and are poorly discretized. That's why before implementing them into any model they need to be interpolated and extrapolated. This paper introduces a new interpolation/extrapolation method based on the idea of integrating more physics into the widespread Jensen and Kristensen's method [6]. It essentially relies on the turbo machinery equation analysis performed by Martin during his PhD thesis [9, 10, 11] and the interpolation and extrapolation strategies that he proposed. In most cases the new strategies presented in this paper rely on improvements of the models he proposed.

The objective of this paper is to present and to validate a numerical model of a single-cylinder pneumatic-combustion hybrid engine. The model presented in this paper contains 0-D sub-models for non-spatially distributed components: Engine cylinder, Air tank, wall heat losses. 1-D sub-models for spatially distributed components are applied on the compressive gas flows in pipes (intake, exhaust and charging). Each pipe is discretized, using the Two-Steps Lax-Wendroff scheme (LW2) including Davis T.V.D. The boundaries conditions used at pipe ends are Method Of Characteristics (MOC) based. In the specific case of a valve, an original intermediate volume MOC based boundary condition is used. The numerical results provided by the engine model are compared with the experimental data obtained from a single cylinder prototype hybrid engine on a test bench operating in 4-stroke pneumatic pump and 4 stroke pneumatic motor modes.

The energy management of a hybrid vehicle defines the vehicle power flow that minimizes fuel consumption and exhaust emissions. In a combined hybrid the complex architecture requires a multi-input control from the energy management. A classic optimal control obtained with dynamic programming shows that thanks to the high efficiency hybrid electric variable transmission, energy losses come mainly from the internal combustion engine. This paper therefore proposes a sub-optimal control based on the maximization of the engine efficiency that avoids multi-input control. This strategy achieves two aims: enhanced performances in terms of fuel economy and a reduction of computational time.

This paper presents the development of torque-based engine control strategies for a downsized SI engine, from simulation design to final validation on a demonstration car. One main issue to reach performance, fuel consumption and pollutant emission demands is in-cylinder mass observation and control. A simulation-based approach is first presented to design accurate observers from a reference simulator. In this study, a multivariable and non-linear control has been developed and focused on in-cylinder mass trajectories. It has been tested on a real time Software-In-the-Loop platform before a complete validation and calibration on the test bed. Finally, the complete torque-based engine control has been successfully integrated on the vehicle.

In the whole engine development process, 0D/1D simulation has become a powerful tool, from conception to final calibration. Within the context of control strategy design, a turbocharged spark ignition (SI) engine with variable camshaft timing has been modelled on the AMESim platform. This paper presents the different models and the methodology used to design, calibrate and validate the simulator. The validated engine model is then used for engine control purposes related to downsizing concept. Indeed, the presented control strategy acts on the in-cylinder trapped mass, the in-cylinder burnt gas fraction and the air scavenging from the intake to the exhaust. Consequently, it permits to reduce not only the fuel consumption and pollutant emissions but also to improve the transient response of the turbocharger

Nowadays, (engine) downsizing using turbocharging appears as a major way for reducing fuel consumption. With this aim in view, the air actuators (throttle, Turbo WasteGate) control is needed for an efficient engine torque control especially to reduce pumping losses and to increase efficiency. This work proposes Nonlinear Model Predictive Control (NMPC) of the air actuators for turbocharged SI engines where the predictions are achieved by a neural model. The results obtained from a test bench of a Smart MCC engine show the real time applicability of the proposed method based on on-line linearization and the good control performances (good tracking, no overshoot) for various engine speeds.