Improvement of Air Quality in Vehicles – Simulation of Two Different Use Cases of HEPA Filtration
Matisse Lesage, David Chalet, Jérôme Migaud, Christoph Krautner, SHIKHAR ARORA, Nilesh Tharval, Martin Lehmann,
MANN+HUMMEL GmbH Abstract Number: 33
Working Group: Control and Mitigation Technology
AbstractThe air quality inside a vehicle is of high interest for the health of humans, particularly for professionals like bus, taxi and truck drivers who spend most of their time on the road. Vehicles operate in rough environments or urban locations with high fine dust concentration. Drivers and vehicle occupants can be exposed to high level of pollution.
The proposed solution to improve the air quality in the vehicle is the Smart Cabin Air Filter system. It introduces a HEPA (High Efficiency Particulate Air) filter in the fresh air path, protected by a pre-filter, in addition to the traditional interior filter in the air conditioning unit. The study focuses on optimizing filter life time. The effect of this smart and sensor driven three-filter system on total energy consumption and driving range will also be part of upcoming studies.
The HEPA filter uses a high-end filtration technology coming from the clean room industry, which plays a major role to limit the concentration of ultra-fine particles in the cabin. In order to maintain its performance at a high level while limiting maintenance costs, its lifespan must be maximised. A system simulation tool is used to compare configurations on elaborated scenarios. The model used is calibrated with experimental data.
Two scenarios will be presented. One is preserving the HEPA filter by using the recirculation mode in the cabin as much as possible. A second scenario is bypassing the HEPA filter when it is not needed to improve air quality, thus reducing the usage of the HEPA element. With this control, the HEPA filter is used only when the fine particle concentration gets too high in the cabin. The simulation results show that this strategy is helpful: the savings are estimated at 60% in terms of usage time, and 48% regarding the particle loading.