Year: 2026
Type: article
Abstract: The complexity of modern vehicle control systems, the increasing diversity of powertrain and exhaust aftertreatment applications, and the need for shortened development times require innovative approaches towards calibration. This paper presents an experimental, analytical, and modeling study of particulate filter (commonly called DPF—diesel particulate filter) in a diesel hybrid vehicle where models have been developed to simulate test data, replacing the requirement of numerous tests on testbed or on the road with system simulations and offline parameter optimisation techniques. A soot estimation model has been developed based on the operation of the engine including its transient response, and the thermal–chemical behaviour of the DPF. A methodology has been developed to optimize the calibratable maps and parameters within this model. The results show that the proposed method improves the accuracy of soot estimation in the engine transient operation and avoids a large number of experimental tests required in traditional calibration methods. Modern automotive manufacturers face regulatory compliance requirements ensuring emission standards across diverse real driving emission (RDE) boundary conditions encompassing route characteristics, driving dynamics, and ambient environmental variables throughout vehicles’ operational lifetime. The soot load in the DPF and the DPF regeneration frequency can massively impact the tailpipe NOx emissions and overall fuel consumption, so it is key to accurately estimate the soot accumulation in all operating conditions. This means testing and validating calibration in each possible scenario and so needs an enormous number of tests on testbed and on the road. These tests, however, can be replaced with system simulations and offline calibration if we have a robust model for the system, as described in the following parts of this paper.
Source: Future Transportation
Institution: Loughborough University
Language: English
Topic: Engine and Fuel Emissions
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W7128775928
FWCI:
Cites:
Cited by:
Related to: