• Energy Research
• 2021-2025close
• Closed Access close
• Open Source close
• Applied Energy close

Abstract Accurate residual capacity estimation of retired LiFePO4 batteries is critically important for second-use applications but is challenging with multiple aging pathways and nonlinear degradation mechanisms. In this study, a fast and accurate residual capacity estimation method based on the mechanism and data-driven model is developed with two main contributions. First, as the basis of the residual capacity estimation model, three new health indicators directly related to the capacity loss mechanism are derived from the prognostic and mechanism model using the Levenberg-Marquardt method and Spearman correlation. Second, residual capacity tests were conducted on 1000 retired batteries to establish a data-driven model for residual capacity estimation based on the proposed health indicators, guaranteeing better universality and estimation accuracy for different types of retired LiFePO4 batteries. To establish a data-driven model for the residual capacity estimation, an improved moth–flame optimization and support vector regression method is used; the adaptive weight and Levy flight are introduced in the moth–flame optimization algorithm to prevent the local optimal value. The residual capacity estimation results are compared with the results from three other typical methods and input health indicators. The results show that the root mean square error of the proposed method is within 2.18% using only the first 10% of the data, a smaller error than with the other methods. A fast and accurate residual capacity estimation method for retired batteries can reduce the cost and improve the development for second-use applications.

Abstract Metal hydride (MH) has been of great interest as one of the potential thermochemical heat storage materials. Previous studies have revealed that with the progress of the reaction, the inhomogeneous reaction will gradually appear in the metal hydride heat storage reactor (MHHSR), which will lead to the decrease of the heat output capacity of the reactor. In this study, an innovative MHHSR with a variable cross-section annular fin (VCSAF) structure is proposed. The thermal coupling model between the powder bed and VCSAF is established. It is found that the VCSAF can effectively resolve the inhomogeneous reaction phenomenon in the reaction process by adjusting the inclination angle between outer profile of VCSAF and outer edge of bed (θfin). At the same time, the influence of different fin structures parameters is analyzed on the uniformity of the reactor based on sensitivity analysis. The width of the largest fin (Lfin,max) is the main factor affecting the uniformity in comparison with fin thickness (hfin), fin spacing (Δh). With the increase of Lfin,max, Δh and hfin, exergy output (Ex,out) changes from 266.12 kJ to 249.65 kJ, 222.64 kJ to 282.99 kJ, and 264.01 kJ to 255.82 kJ, respectively, gravimetric exergy-output power of reactor (GEOPR) changes from 41.96 W kg−1 to 48.22 W kg−1, 49.88 W kg−1 to 42.41 W kg−1, and 43.11 W kg−1 to 47.40 W kg−1, respectively, and gravimetric efficient exergy-output (GEEO) remains unchanged. Besides, the simulation results of four different designs: no fin (NF), same cross-section fin (SCSF), longitudinal fin (LF) and VCSAF are compared to assess their performance. Compared to NF, SCSF and LF, VCSAF has a more uniform heat transfer effect and better performance. Finally, the performance improvement of the enlarged VCSAF reactor is analyzed. With the increase of length (L), the platform end time difference between the SCSF and VCSAF and between LF and VCSAF (Δt1 and Δt2) increases from 800 s to 2800 s and 2250 s to 4800 s, respectively. Compared with NF, the growth rates of Ex,out, exergy efficiency (ηEx), GEEO and GEOPR for VCSAF change from 4.04% to 16.07%, 6.79% to 14.42%, 10.60% to 22.22%, and 31.74% to 6.81%, respectively. Compared with SCSF, the growth rates of Ex,out, ηEx, GEEO and GEOPR change from 12.41% to 26.23%, 9.74% to 17.97%, 12.54% to 26.01%, and 5.00% to 2.18%, respectively. Compared with LF, the growth rates of Ex,out, ηEx, GEEO and GEOPR change from 14.52% to 34.02%, 10.12% to 20.18%, 13.53% to 27.99%, and 7.70% to 5.56%, respectively. The VCSAF structure has an excellent performance in eliminating inhomogeneous reaction. With the enlargement of the reactor, the heat output capacity has been improved obviously, which has an important guiding significance for the engineering application of the MH high-temperature heat storage technology.

Abstract In this work, the design, fabrication and test of a novel Origami-inspired triboelectric nanogenerator (TENG) are presented. The excellent performance of the proposed Origami-TENG is attributed to its stacked architecture and, thereby, the enlarged effective contact area. The mechanism of effective area enlargement is explained through mathematical proof. The strips used to fabricate the Origami structure are engineered with three layers. For one of the three-layered strips, the top and bottom layers are triboelectric materials with strong negative charge affinities. The middle layer is made of conductive material to constitute the electrode for collecting and guiding the charges induced on the surfaces of the triboelectric materials. The other three-layered conductive strip plays the role of the electrode with a middle polymer layer to provide high flexibility. The performance improvement is validated by the experimental results. Under a periodic tap excitation, the root-mean-square voltage of the proposed Origami-TENG is much larger than that of a conventional counterpart. Moreover, it has been found that by increasing the tapping speed and force, the voltage output from the proposed Origami-TENG can be increased. According to evaluation, the proposed Origami-TENG can produce a power output of around 200 μW. In two application tests, the proposed Origami-TENG can easily light up 28 LEDs and generate sufficient energy in about 40 s to power an electronic device - ViPSN, i.e., a programmable Internet-of-Things sensor node.

Abstract In a tidal power plant the most important devices are the tidal current turbines that harvest the kinetic energy contained in the tide and convert it into electricity. The number of turbines to install, their spatial configuration, and the connection of submarine cables are critical aspects in the development of marine energy projects. Here, we present a mixed-integer programming methodology to design tidal current farms considering both cost and benefits. We propose a model that solves, concurrently, the turbine’s locations and cable infrastructure by computing the number, locations, submarine connections of tidal turbines, and the tidal current farm’s overall capacity. The proposed model considers location-based costs, including cable routing and loss from wake effect and electrical transmission, to maximize the project’s economic viability. We demonstrate the methodology’s utility by determining the optimal turbines’ configuration in a real-life case study in the Chacao Chanel, Chile. Finally, practitioners can easily implement our methodology using any standard off-the-shelf mixed-integer programming software to evaluate their tidal current farm projects.