268167 Optimal Temperature Control Using Latent Energy Storage
Optimal Temperature Control Using Latent Energy Storage
Siyun Wang and Michael Baldea
Department of Chemical Engineering
The University of Texas at Austin, 1 University Station C0400, Austin, TX 78712
An ever increasing number and broader range of mobile devices in industrial and consumer applications (e.g., wireless sensors, cellular phones, mobile computers, electric vehicles), depend on battery power to fulfill their function. Their utility depends strongly on the useful battery life - on the amount of time the device can operate until the battery must be recharged. Useful battery life can, evidently, be increased by increasing the stored energy (that is, by increasing battery capacity), which, at present, can entail a significant cost and carry an unacceptable weight penalty (Armand & Tarascon, 2008). The alternative lies in improving the way the stored energy is used, i.e., improving system energy management.
The operation of mobile devices is typically intermittent, ranging from a low-energy “standby” mode, to a high-intensity operation when the system operates at full capacity. The latter is often associated with a high rate of heat generation (Chen, Wu, & Hwang, 2008) (for example, heat output from central/graphics processors in a portable computer increases dramatically under full load; likewise, batteries installed in electric or hybrid vehicles require significant cooling under hard acceleration or during charging). High intensity operation is typically accompanied by the activation of cooling devices, typically fans, to maintain the device temperature within an acceptable range. In turn, active cooling reduces the battery charge and the total operation time of the mobile device.
In this work, we present a novel approach for temperature control and diminishing active cooling needs via latent energy storage. We consider an energy storage medium located in direct contact with the heat source of the system (e.g., processor, battery), which acts as a buffer that absorbs –at constant temperature – the heat generated during high-intensity operation. The heat is subsequently dissipated to the environment through a combination of natural and forced convection. Using a simple linear analysis, we demonstrate that, in the general case, this concept requires considerably less energy to maintain the temperature of the system at a desired value than the traditional approach based exclusively on forced-convective cooling.
Subsequently, we focus on the use of Phase Change Materials (PCMs) as thermal energy storage media. PCMs present the advantage of a relatively high latent heat and thus an increased storage density (Sharma, Tyagi, Chen, & Buddhi, 2009). In order to increase specific area (and, consequently, to decrease the time required for the PCM to undergo melting/solidification cycles), we consider a particular class of materials, where the PCM is encapsulated in a thermally conductive matrix. We develop a mathematical model capturing the melt dynamics of matrix PCM materials in the most general case, assuming that the PCM particles are polydisperse. Subsequently, we construct a model that describes the behavior of the ensemble consisting of the heat source, the temperature controlled system, the PCM thermal buffer, and a cooling fan, and employ this model to develop an optimal sizing method for the thermal buffer. To this end, we formulate a novel stochastic optimization method, based on a dynamic optimization where disturbances (e.g., heat generation patterns) are described as multi-level random signals.
Finally, we provide a numerical case study concerning the control of the CPU temperature in a portable computer. We show that the proposed latent energy storage temperature control approach yields significant energy savings by reducing fan use. Further, we demonstrate that the optimal size of the required storage buffer (using commercially available PCMs) is sufficiently small to encourage the implementation of this approach in portable devices. Reference
Armand, M., & Tarascon, J. (2008). Building better batteries. Nature, pp. 652-657.
Chen, C.-T., Wu, C.-K., & Hwang, C. (2008). Optimial Design and Control of CPU Heat Sink Processes. IEEE Transactions on Components and Packaging Technologies, pp. 184-195.
Sharma, A., Tyagi, V., Chen, C., & Buddhi, D. (2009). Review on thermal energy storage with phase change materials and applications. Reneewable and Sustainable Energy Reviews, 318 - 345.