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Simulink Model for LMV and Conceptualization of 2 Speed E-Axle

Paper No.: 2024-AC-06
Authors: null Rohan Sandeep Mahatekar; null Ritwik Pulikkal Kizhakkeyil; null Sohail Sarfraj Sayyed; null Omkar Jeevanprakash Ankalkope; null Dr. Virendra Bhojwani;

Simulink Model for LMV and Conceptualization of 2 Speed E-Axle

Abstract

Heavy-duty trucks are the primary contributor to the global emissions of greenhouse gases. Because of this, electric haulage has seen significant growth in popularity. Electric heavy-duty trucks aren't widely adopted because of their limited range, payload capacity, and high prices. Electric axle systems, sometimes known as "E-Axles," are capable of electrifying heavy-duty vehicles effectively. The motor, power electronics, and gearbox are all combined into one unit in an E-axle. E-axles that are devoid of motors and gearboxes have the potential to boost performance while also reducing weight and fuel consumption. Heavy-duty automobiles are similar to them. E-axles have the potential to increase the fuel efficiency, flexibility, and emissions of heavy-load trucks. The e-axles are being inspected. E-axles for heavy-duty trucks bring both issues and opportunities concerning finances, infrastructure, and costs. Examine the performance standards as well as the technology behind batteries. This paper provides an introduction to MATLAB Simulink, which focuses on engineering and science. Simulink facilitates the design, simulation, and evaluation of systems. This article demonstrates the fundamental principles, features, and benefits of Simulink through the application of system modeling, control design, and dynamic simulation. It presents Simulink methodologies, libraries, and blocks, as well as interactive simulations. Keywords: MATLAB, Simulink, EV Control systems, EV simulation, EV powertrain modeling, EV test and validation Simulink, WLTP drive cycle

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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