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Due to the rapid development in the technological aspect of the autonomous vehicle (AV), there is a compelling need for research in the field vehicle efficiency and emission reduction without affecting the performance, safety and reliability of the vehicle. Electric vehicle (EV) with rechargeable battery has been proved to be a practical solution for the above problem. In order to utilize the maximum capacity of the battery, a proper power management and control mechanism need to be developed such that it does not affect the performance, reliability and safety of vehicle. Different optimization techniques along with deterministic dynamic programming (DDP) approach are used for the power distribution and management control. The battery-operated electric vehicle can be recharged either by plug-in a wired connection or by the inductive mean (i.e. wirelessly) with the help of the electromagnetic field energy.

We also analyze how useful Cybersecurity Assurance Levels (CAL) are in this process and how quantitative as well as qualitative metrics can be utilized as evidence.

The authors previously presented at SAE 2015, the use of acoustic diagnostic network algorithms (Acoustic DNA) for the measurement and analysis of noise paths in motor vehicles. To further the understanding of the huge amount of data created in this method, especially by the end user or customer, a secure web based application platform has been engineered. The current paper presents operating aspects of the web based approach, including cyber security, multi device accessibility and intuitive user interface together with an innovative optimization toolbox from which both noise sources and vehicle body systems can be modified to be target compliant.

Software vulnerability management is one of the most critical and crucial security techniques, which analyzes the automotive software/firmware across the digital cockpit, ADAS, V2X, etc. domains for vulnerabilities, and provides security patches for the concerned Common Vulnerabilities and Exposures (CVE). The process of automotive SW/FW vulnerability management system between the OEMs and vendors happen through a channel of fixing a certain number of vulnerabilities by 1st tier supplier which needs to be verified in front of OEMs for the fixed number and type of patches in there deliverable SW/FW. The gap of verification between for the fixed patches between the OEMs and 1st tier supplier requires a reliable human independent intelligent technique to have a trustworthiness of verification.