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UID:pretalx-amfc2026-SXPFPM@modelica.simtek.cc
DTSTART;TZID=CST:20260922T144000
DTEND;TZID=CST:20260922T150500
DESCRIPTION:With the continuous growth in global sales and market penetrati
 on\, electric vehicles are increasingly required to operate under extreme 
 temperatures\, high altitudes\, and humid or saline conditions\, posing su
 bstantial challenges to thermal management. To address this challenge\, th
 is paper proposes a 1D model-based framework for integrated thermal manage
 ment system (ITMS)\, enabling the unified design of modeling\, simulation\
 , and control. A vehicle-level thermal model is developed in Modelica to c
 apture the coupled dynamics of the refrigeration cycle\, cabin\, battery\,
  and motor\, and is driven by driving cycles to simulate diverse operating
  conditions. The functional mock-up interface (FMI) is adopted to bridge t
 he physical simulation model and the co-simulation environment\, establish
 ing a control interface that supports multivariable coordination and facil
 itates the integration of data-driven methodologies\, such as reinforcemen
 t learning (RL). Within this framework\, a RL-based control model is imple
 mented to coordinate the system’s actuators. Under dynamic driving cycle
 s\, we evaluate the learned RL policy against a fixed-parameter baseline a
 nd a rule-based controller. The results validate the feasibility of the pr
 oposed integrated architecture in coupling physicsbased level modeling wit
 h adaptive data-driven control\, providing a systematic approach for therm
 al management design in electric vehicles.
DTSTAMP:20261004T070755Z
LOCATION:(Electric) Mobility & Buildings (R2003)
SUMMARY:Model-Based Thermal Management for Electric Vehicles: Modeling\, Si
 mulation\, and Control - Chengen Li\, Zhixu Chen\, Li Xie\, Xiaohu Wang\, 
 Yuxi Liu\, Yuanhao Piao
URL:https://modelica.simtek.cc/amfc2026/talk/SXPFPM/
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