A New Approach to Functional and Software Structure for Engine Management Systems - BOSCH ME7

Gerhardt, Jürgen; Hönninger, Harald; Bischof, H.

doi:10.4271/980801

Cited by 69 publications

(33 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The feature-modeling method introduced earlier in this paper was used to analyze the functionality of the software of the Motronic control system for gasoline engines [13,14].…”

Section: Feature Modeling For Engine Control Softwarementioning

confidence: 99%

Feature Interaction and Dependencies: Modeling Features for Reengineering a Legacy Product Line

Ferber

Haag

Savolainen

2002

Software Product Lines

View full text Add to dashboard Cite

Abstract. Reengineering a legacy product line has been addressed very little by current product line research activities. This paper introduces a method to investigate feature dependencies and interactions, which restricts the variants that can be derived from the legacy product line assets. Reorganizing the product line assets with respect to new requirements requires more knowledge than what is easily provided by the classical feature-modeling approaches. Hence, adding all the feature dependencies and interactions into the feature tree results in unreadable and unmanageable feature models that fail to achieve their original goals. We therefore propose two complementary views to represent the feature model. One view shows the hierarchical refinement of features similar to common featuremodeling approaches in a feature tree. The second view describes what kind of dependencies and interactions there are between various features. We show two examples of feature dependencies and interactions in the context of an engine-control software product line, and we demonstrate how our approach helps to define correct product configurations from product line variants.

show abstract

“…The feature-modeling method introduced earlier in this paper was used to analyze the functionality of the software of the Motronic control system for gasoline engines [13,14].…”

Section: Feature Modeling For Engine Control Softwarementioning

confidence: 99%

Feature Interaction and Dependencies: Modeling Features for Reengineering a Legacy Product Line

Ferber

Haag

Savolainen

2002

Software Product Lines

View full text Add to dashboard Cite

show abstract

“…There, the base ignition angle is equal to the MBT ignition angle. As measurement results shown in [11] indicate, the decrease in torque for ignition angles other than MBT can be well approximated with a second order function. At high engine loads the ignition angle can only be retarded because engine knock must be avoided.…”

Section: Test Bench Implementationmentioning

confidence: 78%

“…where k ign depends on the engine design and is independent of the operating point of the engine [11]. A very low ignition efficiency leads to a large retardation of the ignition angle.…”

Section: Ignition Controllermentioning

confidence: 99%

Intake Manifold Boosting of Turbocharged Spark-Ignited Engines

et al. 2013

View full text Add to dashboard Cite

Downsizing and turbocharging is a widely used approach to reduce the fuel consumption of spark ignited engines while retaining the maximum power output. However, a substantial loss in drivability must be expected due to the occurrence of the so-called turbo lag. The turbo lag results from the additional inertia that the turbocharger adds to the system. Supplying air by an additional valve, the boost valve, to the intake manifold can be used to overcome the turbo lag. This turbo lag compensation method is referred to as intake manifold boosting. The aims of this study are to show the effectiveness of intake manifold boosting on a turbocharged spark-ignited engine and to show that intake manifold boosting can be used as an enabler of strong downsizing. Guidelines for the dimensioning of the boost valve are given and a control strategy is presented. The trade-off between additional fuel consumption and the consumption of pressurized air during the turbo lag compensation is discussed. For a load step at 2000 rpm the rise time can be reduced from 2.8 s to 124 ms, requiring 11.8 g of pressurized air. The transient performance is verified experimentally by means of load steps at various engine speeds to various engine loads.

show abstract

“…In this framework, the engine is considered as a torque source [17] with constraints on fuel consumption and pollutant emission. From the global characteristics of the vehicle, the Vehicle layer controls driver strategies and manages the links with other devices (gear box, ...).…”

Section: Common Features In Engine Controlmentioning

confidence: 99%

On Learning Machines for Engine Control

Bloch

Lauer

Colin

2008

Studies in Computational Intelligence

View full text Add to dashboard Cite

Summary. The chapter deals with neural networks and learning machines for engine control applications, particularly in modeling for control. In the first section, some basics on the common features of engine control are recalled, based on a layered engine management structure. Then the use of neural networks for engine modeling, control and diagnosis is briefly described. The need for descriptive models for model-based control and the link between physical models and black box models are emphasized at the end of this section by exposing the grey box approach taken in this chapter. The second section introduces the neural models most used in engine control, namely, MultiLayer Perceptrons (MLP) and Radial Basis Function (RBF) networks. A more recent approach, known as Support Vector Regression (SVR), to build models in kernel expansion form is then presented. The third section is devoted to examples of application of these models in the context of turbocharged Spark Ignition (SI) engines with Variable Camshaft Timing (VCT). This specific context is representative of modern engine control problems. In the first example, the airpath control is studied, where open loop neural estimators are combined with a dynamical polytopic observer. The second example considers modeling the in-cylinder residual gas fraction by Linear Programming SVR (LP-SVR), based on a limited amount of experimental data and a simulator built from prior knowledge. Each example tries to show that models based on first principles and neural models must be joined together in a grey box approach to obtain efficient and acceptable results.

show abstract

A New Approach to Functional and Software Structure for Engine Management Systems - BOSCH ME7

Cited by 69 publications

References 2 publications

Feature Interaction and Dependencies: Modeling Features for Reengineering a Legacy Product Line

Feature Interaction and Dependencies: Modeling Features for Reengineering a Legacy Product Line

Intake Manifold Boosting of Turbocharged Spark-Ignited Engines

On Learning Machines for Engine Control

Contact Info

Product

Resources

About