The automotive industry is currently driven by the megatrends electrification, automated driving and connectivity. To cope with these trends, new functionalities and electrical and/or electronic (E/E) systems need to be developed and deployed. Independent of the implementation of E/E systems, their power input shall be ensured by the power supply system as a shared resource -leading to increased functional safety requirements for power supply systems. If the loss of an item's functionality can lead to a hazardous event, a safety goal (SG) specifying a safety-related availability (SaRA) requirement is derived. Thereby, switching to passive mode typically cannot be considered a safe state. To address an SG specifying a SaRA requirement, fault avoidance, fault forecasting and/or fault tolerance measures can be applied. In the case of fault tolerance measures implemented by redundancy, which leads to fail-active behavior, the performance of the backup system during nominal operation and after the first fault can be further refined. In this study, SaRA in the context of ISO 26262 is evaluated in detail and mapped to an example of the power supply domain.
The automotive industry is currently driven by the megatrends electrification, automated driving, and connectivity. To cope with these trends, new functionalities and electric and/or electronic systems must be developed, which require a safe power supply by the power supply system. This leads to increased functional safety requirements for the power supply system, particularly regarding availability. Fault tolerance measures can be implemented to address a safety goal specifying a safety-related availability requirement. In this case, emergency operation (EO) may be necessary to reach a defined safe state. The definitions and examples provided in ISO 26262 focus on cold redundancy, whereby the backup system is not engaged during nominal operation. The objective of this paper is to evaluate EO in the context of ISO 26262 in detail and map the results to an exemplary power supply system architecture implementing cold redundancy. In general, the EO is considered to be free from unreasonable risk even though the actual automotive safety integrity level (ASIL) capability of the item is lower than the initially specified ASIL rating for the hazard due to its timing restrictions. To determine the maximum permissible duration of EO, not just random hardware faults shall be considered; additionally, systematic effects shall be considered. Furthermore, an EO may be entered due to transient faults potentially causing temporary EOs -introducing the necessity of an EO recording, e.g. by accumulating the time of all temporary EOs.
Statistical power analyses are used in the design of experiments to determine the required number of specimens, and thus the expenditure, of a test. Commonly, when analyzing and planning life tests of technical products, only the confidence level is taken into account for assessing uncertainty. However, due to the sampling error, the confidence interval estimation varies from test to test; therefore, the number of specimens needed to yield a successful reliability demonstration cannot be derived by this. In this paper, a procedure is presented that facilitates the integration of statistical power analysis into reliability demonstration test planning. The Probability of Test Success is introduced as a metric in order to place the statistical power in the context of life test planning of technical products. It contains the information concerning the probability that a life test is capable of demonstrating a required lifetime, reliability, and confidence. In turn, it enables the assessment and comparison of various life test types, such as success run, non-censored, and censored life tests. The main results are four calculation methods for the Probability of Test Success for various test scenarios: a general method which is capable of dealing with all possible scenarios, a calculation method mimicking the actual test procedure, and two analytic approaches for failure-free and failure-based tests which make use of the central limit theorem and asymptotic properties of several statistics, and therefore simplify the effort involved in planning life tests. The calculation methods are compared and their respective advantages and disadvantages worked out; furthermore, the scenarios in which each method is to be preferred are illustrated. The applicability of the developed procedure for planning reliability demonstration tests using the Probability of Test Success is additionally illustrated by a case study.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.