Spatially Distributed Programmable Morphing Surfaces in Conjunction with Electrochemical Energy Storage within the Structure
Name: Souvik Mukhopadhyay
Spatial control of actuation relies on the deformation of continuous surfaces in aerospace and automotive applications. Spatially discretized actuation strategies are limited to larger size, higher weight, and power considerations. Contemporary morphing solutions partition the surface or volume into finite segments and employ finite actuators to drive kinematic linkages in each segment, or employ multi-stable geometries. All these approaches tend to perform a limited set of bespoke functions rather than achieving the versatility of a true morphing surface solution. Spatially discretized actuation can be realized by distributed actuators. To overcome the limitations of current approaches, this thesis presents a digital logic-inspired approach for controlled, spatially discretized, distributed deformation in a structure. Each actuation element is referred to as an AXEL. The density of axels determines the precision achievable through spatially distributed actuation. The actuation can be self-powered if the energy required to drive these axels is stored within the same structure. An electrochemical energy storage unit or a battery is ideal for this application. To minimize the constraints on the morphing, the battery needs to be compliant and be able to withstand the structural loading. The axel array along with this structural battery can lead to self-powered, programmable morphing of the whole structure. The two parts of the multifunctional structure – programmable actuation array and structural energy storage, have been studied separately in this dissertation. The digitally programmable distributed axel array has been driven using a voltage source and an electronic circuit external to the structure. This circuit consists of fundamental logic gates (NAND, NOR) and op-amps. Depending on the arrangement of the circuit elements, the command signal can be relayed to the axels in various ways to construct either an extensional or a bending axel. The structural energy storage is developed as a rechargeable Li-ion cell with carbon fiber anode, polymer electrolyte, and metal oxide cathode. ii This dissertation research aims to first build and characterize a spatially discretized morphing surface, envisioned to be driven by a structural processing unit. It also aims to develop the electrochemical energy storage unit capable of powering the morphing as well as being integrated in the same structure as the actuators. By supplying scalable number of binary digit (bit) inputs to the axels, this spatially discretized actuation platform can be programmed to morph into pre-determined shapes. Besides powering the actuators, the structural battery in itself can also be utilized with great effectiveness to reduce the weight of the battery pack in an EV by enabling multifunctional energy storage in carbon fiber reinforced panels as part of the vehicular structure. To demonstrate the concept of distributed programmable actuation in a simulated environment first, a 7×7 distributed axel array has been built in Simulink. A bending type axel has been modeled using two linear piezo stack actuators placed on top of each other where upward and downward bending has been achieved by supplying voltages of opposite sense to the top and the bottom layer. An op-amp circuitry has been employed to amplify CMOS-level voltage to suitable voltage for piezo actuators. A 2×2 distributed axel array has been fabricated on Teflon substrate with PVDF bimorph actuators. The digital control has been implemented using OptoMOS architecture solid-state relay switches and NI LabView on PC. Simple binary (1/0) operations of the switches have been utilized to formulate a 4-bit input command to generate 2𝑁 shapes. Distinct output responses corresponding to 16 different input combinations have been demonstrated for harmonic excitation. Flexible gel electrolyte for the structural battery has been fabricated by free radical polymerization of a solution containing the monomer or polymer molecules, reaction initiator, and Li+ salt in an organic solvent. The gel polymer electrolyte (GPE) samples have been tested individually for ionic conductivity, mechanical strength, and elongation. The GPE was further characterized by measuring the charge transfer impedance offered by a Li/GPE interface in a symmetric cell with two Lithium metal electrodes. The increase in iii interfacial impedance with deterioration of interface due to cycling was also measured. Specific capacity and Coulombic efficiency for three different types of carbon fibers have been estimated from cyclic lithiation-delithiation of each of them as an electrode in standard cell settings. Structural battery cells have been put together using carbon fiber (CF) electrode, GPE and Lithium metal anode or Li-metal oxide cathode. Cells with UV-polymerized GPE have been assembled in a Swagelok cell. Whereas thermally cured GPE cells have been made in pouch cell format. The delithiation performance achieved for the UV-cured cells has been subpar overall because of poor electrode/electrolyte interface quality on the ‘non-CF’ electrode end. However, reasonable delithiation capacity with Coulombic efficiency close to 90% has been achieved in the discharge cycles of the thermally polymerized GPE cells with CF anode and metal oxide cathode. The dissertation demonstrates for the first time a scalable architecture for spatially discretized actuation as well as a prospect of the structure being self-powered. The morphing experiments demonstrate the realization of the programmable actuation platform via commercial-off-the-shelf (COTS) materials and drive electronics. On the other hand, the charge-discharge cycling of the structural battery cells exhibits optimistic results for significant weight saving in the future of EVs, while also revealing the challenges involved in designing multifunctional energy storage.
Zoom Link (or alternative) - if available
https://osu.zoom.us/j/97304177934?pwd=YThVTVhLRVM3RGVKdW05SWhlN1pYdz09 Meeting ID: 973 0417 7934 Password: 748297
Professor Manoj Srinivasan
Professor Noriko Katsube
Professor Vicky Doan-Nguyen