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IEEE Vehicular Technology Magazine
Article . 2019 . Peer-reviewed
License: IEEE Copyright
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Trends in Automotive Electronics [Automotive Electronics]

Authors: João Pedro F. Trovão;

Trends in Automotive Electronics [Automotive Electronics]

Abstract

Automotive computers have been standard devices on cars since the late 1960s. From the management of engine emissions and fuel economy under increasingly stringent standards to the control of the entire driving process, automotive computers are used more and more. The first use of a small computer in a car was for an electronic fuel -injection system developed by Bosch (Gerlingen, Germany) for a 1968 Volkswagen (VW) model. Because the computer was devoted to engine control, it came to be known as an electronic control unit (ECU). Today, ECUs and, more recently, networked powertrain controllers (xCUs) perform millions of calculations per second to solve long equations and decide the best output reference values to maintain optimum vehicle performance. Automotive computers have come a long way from the modest ECU in the 1968 VW, and their next generation will face complex requirements for fully self-driving vehicles. Numerous carmakers are working intensively on their autonomous cars, which will only add to the number of microprocessors that they use. Up-to-date cars include more than 100 microprocessors, and that kind of demand leads tech companies to undertake huge efforts in computer systems and sensor development to push autonomous cars onto our roads.

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    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).
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    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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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!
13
Top 10%
Top 10%
Top 10%
bronze