AVL Focus - Issue 2024

s the EU7 legislation comes into force, the automotive

industry is faced with the task of implementing new

OBM systems, which identify emissions in real time

while considering parameters such as damaged components,

fuel quality, or environmental conditions. This requires robust

calibration and validation procedures, as well as seamless

integration witLoYt inƽYence on otLer veLicle JYnctions. 8Le

3&1 system mYst also Fe verified Fy inservice comTliance

tests as per the EU7 regulations. AVL offers evolutionary and

revolutionary solutions to meet these challenges.

The Evolutionary Approach

This approach builds upon the traditional, existing control unit

functionality, sensors, and empirical models. It emphasizes

the optimization of current OBD systems (on-board diagnosis

systems). Additional logical functions are implemented to

extend the usage of the existing control unit channels for

plausibility checks at system level.

% Trimary strategy oJ tLis aTTroacL is tLe refinement oJ e\isting

sensor technologies (e.g., NOx sensors in diesel vehicles) to

improve their accuracy and reliability when detecting emissions.

The approach also focuses on the optimization of software

algorithms for emissions monitoring and diagnostics, to ensure

that the effect of partly damaged components can be evaluated

correctly at system level. The objective of the evolutionary

approach is to simplify the transition to EU7-compliant OBM

systems.

The Revolutionary Approach

This approach pushes the boundaries of traditional OBD systems

Fy incorTorating virtYali^ation and artificial intelligence %- . %

key innovation in this respect are virtual emissions sensors:

these utilize advanced physics-based or data-driven simulation

models to define emission levels Fased on inTYt Tarameters,

such as engine operation conditions or environmental factors.

Complementing the existing sensors, virtual sensors provide a

costeƾcient and scalaFle solYtion Jor 3&1 imTlementation.

Additionally, algorithms of machine learning are being

imTlemented. 8Le analysis oJ significant volYmes oJ sensor

data in real time allows AI-based OBM systems to detect

patterns indicating emission violations or malfunctions. This

enaFles Totential issYes to Fe detected and fi\ed at an early

stage. The result is improved overall reliability and effectiveness

of OBM systems, while maintaining compliance with EU7

legislation. The models also map aging effects and production

scatter bands, allowing the system to react more robustly to

attempted manipulation, and form a sound basis for predictive

maintenance.ɸ

– The Future of On-Board Monitoring

Powerful on-board monitoring systems (OBM systems) are a key

instrument for compliance with the new EU7 legislation. AVL offers

a range of approaches tailored to these specific requirements.

Evolution vs.

Revolution

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