System design and analysis methods for optimal electric vehicle thermal management
Singh, Sagar
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Permalink
https://hdl.handle.net/2142/120353
Description
Title
System design and analysis methods for optimal electric vehicle thermal management
Author(s)
Singh, Sagar
Issue Date
2023-04-16
Director of Research (if dissertation) or Advisor (if thesis)
Miljkovic, Nenad
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Electric vehicle
thermal management system
heat pump
waste heat recovery
direct
indirect
general integrated loop
driving range
Abstract
The thermal management system (TMS) in an electric vehicle (EV) encounters many challenges due to the stringent thermal requirements of EV components and concurrent range reduction in cold conditions. Efficient systems require thermal architectures with highly interconnected components to satisfy a wide range of operating conditions. A need exists to develop a methodology which can enable analysis-driven design decisions by leveraging a simulation framework to capture dynamic physical interactions. Here, a versatile simulation framework is developed inside MATLAB-Simulink using Simscape for transient analysis of coolant and refrigerant thermal systems and is validated at both the component and system-levels. A decision tree for EV TMS design is developed to evaluate various trade-offs. Direct and indirect configurations for cabin conditioning are analyzed to compare relative performance. The indirect configuration is found to have a 1.6-1.8x longer conditioning time and a coefficient of performance (COP) decrease of 18-31% and 31-41% for heating and cooling, respectively. A previously unexplored general integrated loop architecture is formulated for concept-level analysis of various EV TMS configurations. Operating modes are formulated for all possible driving conditions and are switched with a control strategy. A detailed analysis is done for an idealized system to study the system-level performance, and important modes are identified by creating a histogram analysis for different driving conditions. Various heat pump (HP) waste heat recovery (WHR) configurations are compared against each other and with coolant based positive temperature coefficient (PTC) heaters for different drive cycles, grades, and ambient temperatures. The range increase of the base HP (with no WHR) configuration relative to PTC heating is found to vary from 4-33% with an extra 1-4.4% possible by using idealized WHR. Waste heat recovery is also shown to improve the HP heating capacity by 28%, making its operation feasible at low temperatures. Applicability of the decision tree in the context of various EV TMS designs of leading manufacturers and existing literature is discussed.
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