Vincent Talon

Physical-Based Algorithms for Interpolation and Extrapolation of Turbocharger Data Maps

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. Thats why before implementing them into any model they need to be interpolated and extrapolated.

Simultaneous Air Fraction and Low-Pressure EGR Mass Flow Rate Estimation for Diesel Engines

Abstract This paper describes a low-pressure exhaust gas recirculation (LP-EGR) mass flow rate estimation method and a robust air mass fraction observer for a Diesel engine with dual-loop EGR system. Both observers operate simultaneously eliminating the need for pressure measurement upstream the LP-EGR valve. A sliding mode observer is designed to estimate the LP-EGR mass flow rate using the standard sensors available in commercial Diesel engines. A robust linear parameter varying Kalman filter is designed for the air mass fraction estimation. The convergence and robustness of the observers are ensured by means of Lyapunov stability and a linear matrix inequality (LMI) framework for the sliding mode observer and robust Kalman filter, respectively. The observers are evaluated with a Motor Vehicle Emission Group (NMVEG) cycle using an engine model validated on an experimental benchmark as a reference.

Validation and Application of a New 0D Flame/Wall Interaction Sub Model for SI Engines

To improve the prediction of the combustion processes in spark ignition engines, a 0D flame/wall interaction submodel has been developed. A two-zones combustion model is implemented and the designed submodel for the flame/wall interaction is included. The flame/wall interaction phenomenon is conceived as a dimensionless function multiplying the burning rate equation. The submodel considers the cylinder shape and the flame surface that spreads inside the combustion chamber. The designed function represents the influence of the cylinder walls while the flame surface propagates across the cylinder. To determine the validity of the combustion model and the flame/wall interaction submodel, the system was tested using the available measurements on a 2 liter SI engine. The model was validated by comparing simulated cylinder pressure and energy release rate with measurements. A good agreement between the implemented model and the measurements was obtained.

Explicit nonlinear model predictive control of the air path of a turbocharged spark-ignited engine

Pollutant emissions and fuel economy objectives have led car manufacturers to develop innovative and more sophisticated engine layouts. In order to reduce time-to-market and development costs, recent research has investigated the idea of a quasi-systematic engine control development approach. Model based approaches might not be the only possibility but they are clearly predetermined to considerably reduce test bench tuning work requirements. In this paper, we present the synthesis of a physics-based nonlinear model predictive control law especially designed for powertrain control. A binary search tree is used to ensure real-time implementation of the explicit form of the control law, computed by solving the associated multi-parametric nonlinear problem.

Fresh Air Fraction Control in Engines Using Dynamic Boundary Stabilization of LPV Hyperbolic Systems

In this paper, we consider the boundary control of the fresh air mass fraction in a Diesel engine operated with low-pressure exhaust gas recirculation. The air mass fraction transport phenomenon is modeled using a cascade of first-order linear parameter-varying hyperbolic systems with dynamics associated with their boundary conditions. By means of Lyapunov-based techniques, sufficient conditions are derived to guarantee the exponential stability of this class of infinite dimensional systems. We develop a polytopic approach to synthesize a robust boundary control that guarantees the exponential stability for a given convex parameter set. Simulation results illustrate the effectiveness of the proposed boundary control to regulate the mass fraction of fresh air in a Diesel engine.

New Physics-Based Turbocharger Data-Maps Extrapolation Algorithms: Validation on a Spark-Ignited Engine

Abstract Objectives in terms of pollutant emissions and fuel consumption reduction, as well as development costs and time to market reduction, has led car manufacturers to use more and more system simulation. However, among all the fields in which it has enabled to achieve these goals, the control development stage is one of those, in which major improvements can still be achieved. In this context and with the increasing penetration of downsized engines, turbocharger modeling has become one of the biggest challenges in engine simulation. This paper focuses on the validation of compressor and turbine data maps, extrapolated using new physics-based extrapolation algorithms. The study led to excellent prediction performances for two classical control-oriented models. Conclusions stress: 1- The improvement of the extrapolation robustness, in particular in the low turbocharger rotational speeds zone. 2- The possibility to keep a low calculation time as well as maintaining the same calibration effort.

Neural Model for Real-Time Engine Volumetric Efficiency Estimation

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 networkbased 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. The calibration process that is used in this study only requires steady-state operating points. The validation stage was conducted on both steady-state and vehicle transients. Model prediction is in very good agreement with experimental results while keeping a very low calibration effort and matching embedded computational requirements. The conclusion stresses that thanks to their generic structure, neural models offer an interesting potential for generalization to even more complex technical definitions.

Nonlinear model predictive control of the air path of a turbocharged gasoline engine using Laguerre functions

Objectives in terms of pollutant emissions and fuel consumption reduction have led car manufacturers to enhance the technical definitions of combustion engines. The latter should now be considered as multiple-input multiple-output nonlinear systems with saturated actuators. This considerably increases the challenge regarding the development of optimal control laws under the constraints of constant cost reductions in the automotive industry. In the present paper, the use of a nonlinear model predictive control (NMPC) scheme is studied for the air path control of a turbocharged gasoline engine. Specifically, a zero dimension physics-based model is combined with parameterization of the future control trajectory. The use of Laguerre polynomials is shown to increase flexibility for the future control trajectory at no cost in computational requirements. This increase in flexibility leads to an improvement of the transient response of the closed-loop with respect to traditional approaches. This practical application shows that this approach makes it easier to fine-tune the NMPC scheme when dealing with engine air path control.

Exhaust Manifold Pressure Estimation Diesel Equipped with a VGT Turbocharger

This paper develops an exhaust manifold pressure estimation method for a Diesel engine equipped with a variable geometry turbine (VGT) turbocharger. Extrapolated VGT data-maps are used directly for the estimation of the exhaust pressure using a non-iterative Newton-Raphson based method suitable for real-time applications. This approach can give more accurate estimations than traditional methods because it takes into account the turbine speed effect on the turbine mass flow rate. All this without increasing the calculation load significantly. The proposed exhaust manifold estimation can be used to relieve the exhaust manifold pressure physical sensor during engine operating conditions where its reliability is low. The estimator is evaluated in transient with two different engine cycles using a engine model validated in a benchmark as a reference.

Intra-Pipe Restriction Non-Homentropic Boundary Resolution Method

A complete non-homentropic boundary resolution method for a flow upstream and downstream an intrapipe restriction is considered in this article. The method is capable of introducing more predictable quasi-steady restriction models into the boundary problem resolution without adding artificial discharge coefficients. The traditional hypothesis of isentropic contraction, typically considered for the boundary resolution, is replaced by an entropy corrected method of characteristics (MOC) in order to be consistent with a non-homentropic formulation. The boundary resolution method is designed independently of the quasi-steady restriction models which allows obtaining a greater modeling flexibility when compared with traditional methods. An experimental validation at unsteady conditions is presented using different restriction quasi-steady models to illustrate the effectiveness of the proposed boundary resolution method in terms of predictability as well as flexibility.