1,721,003 research outputs found
Balancing energy conversion and long-term reliability of dielectric elastomer generators
No full textDielectric elastomer generators (DEG) are soft transducers capable of converting mechanical energy into electrostatic energy. Increasing the mechanical stretch amplitude and the electric field imposed to the DEG leads to higher energy conversion on one hand, but at the cost of a reduced lifetime on the other hand. Here, mechanical fatigue and electrical limits are assessed on a silicone-based DEG and the outcome is used into an electro-mechanical reliability model. The operating parameters (stretch amplitude and electric field) which maximize the energy conversion are obtained from a multi-dimensional optimization approach which gives the best compromise between energetic cycles and long-term reliability. Energy densities reported in the literature are often obtained by pushing the DEG on the knife-edge of their intrinsic capabilities for a limited number of cycles . In contrast, our analysis presents more realistic values in the endurance domain, leading to a substantial reduction of the practical performance that can be achieved
Effect of mechanical loading history on the electrical breakdown strength of dielectric elastomers
No full textOptimizing energy density in dielectric elastomer generators: a reliability-dependent metric
No full textDielectric elastomer generators (DEGs) are soft transducers capable of converting mechanical energy into electrostatic energy. Increasing the mechanical stretch amplitude and the electric field imposed to the DEG leads to higher energy conversion at the cost of a reduced lifetime. Here, mechanical fatigue and electrical degradation were assessed on a silicone-based DEG, and the outcome was used to build an electro-mechanical reliability model. A novel metric, termed levelized energy density, has been introduced to carefully balance the conflicting objectives of high energy output and long-term reliability. Through a multi-dimensional anaylsis of this index, the optimal operating parameters (stretch amplitude and electric field) that maximize energy conversion can be derived. Energy densities reported in literature are generally obtained after pushing the DEG close to their intrinsic limits for a limited number of cycles. In our approach, more realistic values in the endurance domain are presented, which typically leads to a 9-fold decrease in energy density for a design life of 1 million cycles. This article not only addresses the challenge of optimizing DEG performance but also emphasizes the importance of considering realistic operational conditions to enhance reliability, ultimately contributing to the practical and sustainable deployment of these soft transducers in various applications.</p
Why residual life estimation and maintenance strategies for electrical insulation systems have to rely upon condition monitoring
No full textThere is no doubt that the electrical and thermal stress conditions in modern electrical networks are becoming much more challenging than in the past. The presence of voltage transients and power electronics, especially in grids involving renewables, is stressing insulation systems in a not-conventional and often not-predictable way. This paper is looking at the potential effect on insulation aging of repetitive voltage transients, in the presence or absence of partial discharges, raising the point that such transients can cause significant aging acceleration, thus reduce life considerably with respect to the design life. This is why condition monitoring becomes a must: the health of an insulation system has to be evaluated dynamically as a function of time, in order to approach in the most convenient way the matter of maintenance and asset reliability. A general approach to aging under non-sinusoidal waveforms is presented here, referring to both phenomenological and probabilistic algorithms, and examples are reported for speed-controlled rotating machines and train transmission lines. It is emphasized that the aging processes in a transformer will require a more complex modeling approach
Monitoring HV transformer conditions: The strength of combining various diagnostic property observations
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