TY - BOOK ID - 136350890 TI - Future Powertrain Technologies AU - Rinderknecht, Stephan AU - Jardin, Philippe AU - Esser, Arved PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - degree of hybridization KW - energy management KW - hybrid propulsion KW - proton exchange membrane fuel cell KW - simulink, supercapacitor KW - fleet transition KW - optimization KW - life-cycle assessment KW - greenhouse gas KW - global warming potential KW - vehicle powertrain concepts KW - dedicated hybrid transmission KW - benchmarking KW - hybrid electric vehicle KW - efficiency KW - topology optimization KW - drive train optimization KW - powertrain concepts KW - structural reliability KW - uncertainties KW - ensemble learning KW - fault diagnosis KW - VFS KW - GA KW - input feedforward KW - fault observation KW - pressure sensor KW - aftermarket hybridization kit KW - emissions mitigation KW - local driving cycle KW - plug-in hybrid electric vehicles KW - vehicle efficiency KW - plug-in hybrid electric vehicle KW - electromechanical coupling KW - electrified mechanical transmission KW - multi-purpose vehicle KW - machine learning KW - powertrain control KW - automatic re-training KW - hybrid electric vehicles KW - dynamic programming KW - transmission KW - vehicle emissions KW - particle measurement programme (PMP) KW - portable emissions measurement systems (PEMS) KW - volatile removal efficiency KW - non-volatiles KW - solid particle number KW - catalytic stripper KW - evaporation tube KW - artefact KW - E-Mobility KW - powertrain design KW - high-speed KW - electric machine design KW - transmission design KW - gearbox KW - electric vehicles KW - range extenders KW - zinc–air battery KW - lithium-ion battery KW - electric vehicle transition KW - Arrhenius model KW - losses KW - mission profile KW - inverter KW - powertrain KW - Rainflow algorithm KW - reliability KW - thermal network KW - electric vehicle KW - n/a KW - zinc-air battery UR - https://www.unicat.be/uniCat?func=search&query=sysid:136350890 AB - Among the various factors greatly influencing the development process of future powertrain technologies, the trends in climate change and digitalization are of huge public interest. To handle these trends, new disruptive technologies are integrated into the development process. They open up space for diverse research which is distributed over the entire vehicle design process. This book contains recent research articles which incorporate results for selecting and designing powertrain topology in consideration of the vehicle operating strategy as well as results for handling the reliability of new powertrain components. The field of investigation spans from the identification of ecologically optimal transformation of the existent vehicle fleet to the development of machine learning-based operating strategies and the comparison of complex hybrid electric vehicle topologies to reduce CO2 emissions. ER -