Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles
This paper presents a novel fuzzy deterministic noncontroller type (FDNCT) system and an FDNCT inference algorithm (FIA). The FDNCT uses fuzzy inputs and produces a deterministic non-fuzzy output. The FDNCT is an extension and alternative for the existing fuzzy singleton inference algorithm. The res...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2012/687652 |
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| _version_ | 1832547417444057088 |
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| author | Macam S. Dattathreya Harpreet Singh Thomas Meitzler |
| author_facet | Macam S. Dattathreya Harpreet Singh Thomas Meitzler |
| author_sort | Macam S. Dattathreya |
| collection | DOAJ |
| description | This paper presents a novel fuzzy deterministic noncontroller type (FDNCT) system and an FDNCT inference algorithm (FIA). The FDNCT uses fuzzy inputs and produces a deterministic non-fuzzy output. The FDNCT is an extension and alternative for the existing fuzzy singleton inference algorithm. The research described in this paper applies FDNCT to build an architecture for an intelligent system to detect and to eliminate potential fires in the engine and battery compartments of a hybrid electric vehicle. The fuzzy inputs consist of sensor data from the engine and battery compartments, namely, temperature, moisture, and voltage and current of the battery. The system synthesizes the data and detects potential fires, takes actions for eliminating the hazard, and notifies the passengers about the potential fire using an audible alarm. This paper also presents the computer simulation results of the comparison between the FIA and singleton inference algorithms for detecting potential fires and determining the actions for eliminating them. |
| format | Article |
| id | doaj-art-2a130054c9574e719a3673b633dcb19a |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-2a130054c9574e719a3673b633dcb19a2025-02-03T06:44:43ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2012-01-01201210.1155/2012/687652687652Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric VehiclesMacam S. Dattathreya0Harpreet Singh1Thomas Meitzler2Tank Automotive Research, Development and Engineering Center, Warren, MI 48397, USADepartment of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USATank Automotive Research, Development and Engineering Center, Warren, MI 48397, USAThis paper presents a novel fuzzy deterministic noncontroller type (FDNCT) system and an FDNCT inference algorithm (FIA). The FDNCT uses fuzzy inputs and produces a deterministic non-fuzzy output. The FDNCT is an extension and alternative for the existing fuzzy singleton inference algorithm. The research described in this paper applies FDNCT to build an architecture for an intelligent system to detect and to eliminate potential fires in the engine and battery compartments of a hybrid electric vehicle. The fuzzy inputs consist of sensor data from the engine and battery compartments, namely, temperature, moisture, and voltage and current of the battery. The system synthesizes the data and detects potential fires, takes actions for eliminating the hazard, and notifies the passengers about the potential fire using an audible alarm. This paper also presents the computer simulation results of the comparison between the FIA and singleton inference algorithms for detecting potential fires and determining the actions for eliminating them.http://dx.doi.org/10.1155/2012/687652 |
| spellingShingle | Macam S. Dattathreya Harpreet Singh Thomas Meitzler Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles Advances in Fuzzy Systems |
| title | Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles |
| title_full | Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles |
| title_fullStr | Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles |
| title_full_unstemmed | Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles |
| title_short | Detection and Elimination of a Potential Fire in Engine and Battery Compartments of Hybrid Electric Vehicles |
| title_sort | detection and elimination of a potential fire in engine and battery compartments of hybrid electric vehicles |
| url | http://dx.doi.org/10.1155/2012/687652 |
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