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Embedded Software Reliability Modeling for Energy-Critical EV Functions

Author(s) Abhishek Devgan
Country India
Abstract The increasing trends of electric vehicles (EVs) in the global transportation systems have increased the need to have strong, provable, and certified embedded software systems. Energy-critical functions the functions that include battery state estimation, thermal management, regenerative braking and charging control constitute the most safety-sensitive layers of the EV software stack with software failures having direct effects on passenger safety, vehicle range and grid stability. The present research is a complete framework of reliability modeling of embedded software that controls energy-critical EV functions with the aid of probabilistic analysis of failures, formal safety modelling, and automotive functional safety standards, including ISO 26262 and IEC 61508. The framework proposed uses a multiparadigm framework by incorporating Fault Tree Analysis (FTA), Failure Modes and Effects Analysis (FMEA), Bayesian networks, Markov chain models, dynamic fault trees and multi-state system (MSS) reliability theory to describe and quantify failure modes of EV embedded software architectures. The systematic reliability models in battery management systems such as state of charge (SOC) estimation and state of health (SOH) prediction is carried out, revealing the main gaps in the current models and proposing model-based solutions that will comply with the Automotive Safety Integrity Level-D (ASIL-D) level. The combined reliability modeling framework is effective in improving the quantifiable improvements in EV software reliability, residual risk to less than the 10 -8/h requirement of ISO 26262 ASIL-D compliance, and offers a repeatable approach to automotive software engineers and safety analysts.
Keywords Battery management system (BMS), Fault tree analysis (FTA), Failure modes and effects analysis (FMEA), Automotive safety integrity level (ASIL), Bayesian network Markov chain model State of charge (SOC), estimation State of health (SOH) Thermal runaway.
Field Engineering
Published In Volume 4, Issue 3, March 2023
Published On 2023-03-06
DOI https://doi.org/10.5281/zenodo.20347949
Short DOI https://doi.org/hb48mr
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