It’s not the batteries! Smoke alarm presence and functionality 5-7 years post installation of sealed lithium battery alarms

Smoke alarms with lithium batteries have been marketed as long life or “10 Year Alarms.” Previous work has drawn into question the actual term of functionality for lithium battery alarms. This paper reports on observed smoke alarm presence and functionality in a sample of 158 homes which had participated in a fire department smoke alarm installation program 5-7 years prior to the observations. A total of 394 alarms were originally installed in the 158 homes that completed the revisit. At the time of the revisit, 214 of those alarms were working (54%), 26 were non-working (7%), and 154 were missing (39%). Of the 158 homes that completed the revisit, n=62 (39%) had all their originally installed project alarms up at working at the revisit. Respondents who reported owning their homes and who reported living in their home for 6 or more years were significantly more likely than renters and those living in their homes for 5 or fewer years were more likely to maintain all of their project alarms. Smoke alarm installation programs should consider revisiting homes within 5-7 years post installation to inspect and replace any missing or non-functioning alarms. We recommend programs conducting community risk reduction programs track and plan installations and revisits to improve smoke alarm coverage.

A SOE estimation method for lithium batteries considering available energy and recovered energy

State of energy (SOE) is a critical index of lithium battery. The problem of the inaccurate available energy and recovered energy of lithium battery affects the accuracy of SOE estimation. In order to solve the problem, this paper proposes a method to estimate the available discharge energy of lithium batteries based on response surface model. In this method, the energy efficiency of lithium batteries in different states is obtained by establishing the relationship model of external charge voltage and external discharge voltage, so as to estimate the actual available energy of lithium batteries in different charge states. On this basis, a correction method based on radial basis function (RBF) neural network is proposed to estimate the actual energy released by the recovered energy when the current direction of the battery is changed. The proposed energy correction method is combined with the adaptive particle filter algorithm to estimate SOE. This method is not limited to the assumption of Gaussian function and can accurately predict the noise variance, so as to improve the estimation accuracy of SOE. Simulations under urban dynamometer driving schedule (UDDS) are conducted, and the result shows that the proposed method can effectively estimate the battery energy and improve the accuracy of SOE estimation.

Comparative Analysis of Lithium Iron Phosphate Battery and Ternary Lithium Battery

This article analyses the lithium iron phosphate battery and the ternary lithium battery. With the development of new energy vehicles, people are discussing more and more about the batteries of electric vehicles. Nowadays, electric vehicles mainly use the lithium iron phosphate battery and the ternary lithium battery as energy sources. Existing research and articles have given the current performance of the two batteries but have not systematically compared the two batteries with more details. This article introduces the basic principles, cathode structure, and standard preparation methods of the two batteries by summarizing and discussing existing data and research. The article discusses the two types of batteries and concludes the advantages and disadvantages of the two batteries at the present stage. This article aims to help readers have a more comprehensive understanding of the basic information of the two batteries at this stage and provide theoretical guidance for future research on batteries for electric vehicles.