Robust DPF Regeneration Control for Cost-Effective Small Commercial Vehicles ISUZU MOTORS Germany GmbH

Format:

Conference/Event

Author/Creator:

Eck, Eck, author.

Contributor:

Nakano, Futoshi

Conference Name:

13th International Conference on Engines & Vehicles (2017-09-10 : Capri, Italy)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2017

Summary:

AbstractSmall commercial vehicles (SCV) with Diesel engines require efficient exhaust aftertreatment systems to reduce the emissions while keeping the fuel consumption and total operating cost as low as possible. To meet current emission legislations in all cases, a DOC and DPF and some NOx treatment device (e,g. lean NOx trap or SCR) are required.Creating a cost-effective SCV also requires keeping the cost for the exhaust aftertreatment system as low as possible because the contribution to total vehicle cost is high. By using more sophisticated and more robust operating strategies and control algorithms, the hardware cost can be reduced. To keep the calibration effort at a low level, it is necessary to apply only algorithms which have a time-efficient calibration procedure.This paper will focus on the active regeneration of the DPF. For safe and efficient DPF regeneration, a very reliable and stable DOC out temperature control is required. DOC characteristics and design are often limited by cost and available space but also strongly influence the control requirements and thus the performance. This leads to more sophisticated and more robust control algorithms.In this paper an advanced control algorithm for DOC outlet temperature control for a SCV is presented. The control algorithm applies model-based control and gain-scheduling techniques. An overview over the control algorithm is given and its performance is evaluated on engine test bench, chassis dynamometer and on the public road and compared to the traditional concept which was used before. The results and experiences are presented and analyzed

Notes:

Vendor supplied data

Publisher Number:

2017-24-0123

Access Restriction:

Restricted for use by site license