<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Joint Design and Control of Electric Vehicle Propulsion Systems</dc:title><dc:creator>Verbruggen, Frans; Salazar, Mauro; Pavone, Marco; Hofman, Theo</dc:creator><dc:corporate_author/><dc:editor>null</dc:editor><dc:description>This paper presents models and optimization
methods for the design of electric vehicle propulsion systems.
Specifically, we first derive a bi-convex model of a battery
electric powertrain including the transmission and explicitly
accounting for the impact of its components’ size on the energy
consumption of the vehicle. Second, we formulate the energy-optimal sizing and control problem for a given driving cycle
and solve it as a sequence of second-order conic programs.
Finally, we present a real-world case study for heavy-duty
electric trucks, comparing a single-gear transmission with a
continuously variable transmission (CVT), and validate our
approach with respect to state-of-the-art particle swarm optimization algorithms. Our results show that, depending on
the electric motor technology, CVTs can reduce the energy
consumption and the battery size of electric trucks between up
to 10%, and shrink the electric motor up to 50%.</dc:description><dc:publisher/><dc:date>2020-05-01</dc:date><dc:nsf_par_id>10209482</dc:nsf_par_id><dc:journal_name>European Control Conference</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/</dc:doi><dcq:identifierAwardId>1454737</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>