Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems
Power plants, electric generators, high-frequency controllers, battery storage, and control units are essential in current transportation and energy distribution networks. To improve the performance and guarantee the endurance of such systems, it is critical to control their operational temperature...
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| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2023
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| Online Access: | https://hdl.handle.net/1721.1/148472 |
| _version_ | 1811085834688921600 |
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| author | Saavedra, Jorge Gonzalez Cuadrado, David |
| author2 | Massachusetts Institute of Technology. Gas Turbine Laboratory |
| author_facet | Massachusetts Institute of Technology. Gas Turbine Laboratory Saavedra, Jorge Gonzalez Cuadrado, David |
| author_sort | Saavedra, Jorge |
| collection | MIT |
| description | Power plants, electric generators, high-frequency controllers, battery storage, and control units are essential in current transportation and energy distribution networks. To improve the performance and guarantee the endurance of such systems, it is critical to control their operational temperature within certain regimes. Under standard working conditions, those elements become heat sources either during their entire operational envelope or during given phases of it. Consequently, in order to maintain a reasonable working temperature, active cooling is required. The refrigeration may consist of the activation of internal cooling systems relying on fluid circulation or air suction and circulation pulled from the environment. However, in both scenarios pulling surrounding air or making use of coolant pumps increases the power demand. The augmented power demand has a direct impact on the power plant or electric generator autonomy, while instigating higher power demand and substandard performance from the power electronics and batteries’ compounds. In this manuscript, we present a methodology to efficiently estimate the heat flux load generated by internal heat sources. By accurately and inexpensively computing the heat flux, it is possible to identify the coolant requirements to optimize the use of the available resources. Based on local thermal measurements fed into a Kriging interpolator, we can accurately compute the heat flux minimizing the number of sensors required. Considering the need for effective thermal load description toward efficient cooling scheduling. This manuscript presents a procedure based on temperature distribution reconstruction via a Kriging interpolator to monitor the surface temperature using a minimal number of sensors. The sensors are allocated by means of a global optimization that minimizes the reconstruction error. The surface temperature distribution is then fed into a heat conduction solver that processes the heat flux of the proposed casing, providing an affordable and efficient way of controlling the thermal load. Conjugate URANS simulations are used to simulate the performance of an aluminum casing and demonstrate the effectiveness of the proposed method. |
| first_indexed | 2024-09-23T13:16:23Z |
| format | Article |
| id | mit-1721.1/148472 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:16:23Z |
| publishDate | 2023 |
| publisher | Multidisciplinary Digital Publishing Institute |
| record_format | dspace |
| spelling | mit-1721.1/1484722024-01-23T18:50:25Z Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems Saavedra, Jorge Gonzalez Cuadrado, David Massachusetts Institute of Technology. Gas Turbine Laboratory Power plants, electric generators, high-frequency controllers, battery storage, and control units are essential in current transportation and energy distribution networks. To improve the performance and guarantee the endurance of such systems, it is critical to control their operational temperature within certain regimes. Under standard working conditions, those elements become heat sources either during their entire operational envelope or during given phases of it. Consequently, in order to maintain a reasonable working temperature, active cooling is required. The refrigeration may consist of the activation of internal cooling systems relying on fluid circulation or air suction and circulation pulled from the environment. However, in both scenarios pulling surrounding air or making use of coolant pumps increases the power demand. The augmented power demand has a direct impact on the power plant or electric generator autonomy, while instigating higher power demand and substandard performance from the power electronics and batteries’ compounds. In this manuscript, we present a methodology to efficiently estimate the heat flux load generated by internal heat sources. By accurately and inexpensively computing the heat flux, it is possible to identify the coolant requirements to optimize the use of the available resources. Based on local thermal measurements fed into a Kriging interpolator, we can accurately compute the heat flux minimizing the number of sensors required. Considering the need for effective thermal load description toward efficient cooling scheduling. This manuscript presents a procedure based on temperature distribution reconstruction via a Kriging interpolator to monitor the surface temperature using a minimal number of sensors. The sensors are allocated by means of a global optimization that minimizes the reconstruction error. The surface temperature distribution is then fed into a heat conduction solver that processes the heat flux of the proposed casing, providing an affordable and efficient way of controlling the thermal load. Conjugate URANS simulations are used to simulate the performance of an aluminum casing and demonstrate the effectiveness of the proposed method. 2023-03-10T18:31:29Z 2023-03-10T18:31:29Z 2023-03-03 2023-03-10T14:02:06Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/148472 Sensors 23 (5): 2803 (2023) PUBLISHER_CC http://dx.doi.org/10.3390/s23052803 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ application/pdf Multidisciplinary Digital Publishing Institute Multidisciplinary Digital Publishing Institute |
| spellingShingle | Saavedra, Jorge Gonzalez Cuadrado, David Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems |
| title | Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems |
| title_full | Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems |
| title_fullStr | Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems |
| title_full_unstemmed | Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems |
| title_short | Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems |
| title_sort | thermal sensor allocation for effective and efficient heat transfer measurements in transportation systems |
| url | https://hdl.handle.net/1721.1/148472 |
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