Project Title

Autonomous Vehicle Fleet Communication and Battery Dependency

Presenters

Hakeem WilsonFollow

Academic department under which the project should be listed

SPCEET - Engineering Technology

Faculty Sponsor Name

Billy Kihei

Abstract (300 words maximum)

In recent years, the concept of autonomous electric vehicles has taken the automotive industry by storm. Yet, there are a few large concerns that still hinder the progression of this technology. The first would be the safety of a car that drives with no user input. Secondly, many consumers suffer from fear of range anxiety in electric vehicles. However, with the advent of Vehicle to Everything (V2X) communication, it is possible to integrate cars into a shared communication network where a plethora of safety information can be stored and shared, thus allowing cars to interact with each other to create a safer driving environment. As battery technology continues to improve, smart battery monitoring also improves. By monitoring the system loads, battery state of charge, depth of discharge and estimated life remaining can all be calculated and used to optimize battery life and health.

Project Type

Event

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Autonomous Vehicle Fleet Communication and Battery Dependency

In recent years, the concept of autonomous electric vehicles has taken the automotive industry by storm. Yet, there are a few large concerns that still hinder the progression of this technology. The first would be the safety of a car that drives with no user input. Secondly, many consumers suffer from fear of range anxiety in electric vehicles. However, with the advent of Vehicle to Everything (V2X) communication, it is possible to integrate cars into a shared communication network where a plethora of safety information can be stored and shared, thus allowing cars to interact with each other to create a safer driving environment. As battery technology continues to improve, smart battery monitoring also improves. By monitoring the system loads, battery state of charge, depth of discharge and estimated life remaining can all be calculated and used to optimize battery life and health.