Previous research identified that battery temperature control is critical to the safety, lifetime, and performance of electric vehicles. In this paper, the liquid-based battery temperature control of electric buses is investigated subject to heat transfer behavior and control strategy. Therefore, a new transient calculation method is proposed to simulate the thermal behavior of a coolant-cooled battery system. The method is based on the system identification technique and combines the advantage of low computational effort and high accuracy. In detail, four transfer functions are extracted by a thermo-hydraulic 3D simulation model comprising 12 prismatic lithium nickel manganese cobalt oxide (NMC) cells, housing, arrestors, and a cooling plate. The transfer functions describe the relationship between heat generation, cell temperature, and coolant temperature. A vehicle model calculates the power consumption of an electric bus and thus provides the input for the transient calculation. Furthermore, a cell temperature control strategy is developed with respect to the constraints of a refrigerant-based battery cooling unit. The data obtained from the simulation demonstrate the high thermal inertia of the system and suggest sufficient control of the battery temperature using a quasi-stationary cooling strategy. Thereby, the study reveals a crucial design input for battery cooling systems in terms of heat transfer behavior and control strategy.
Vapor compression systems (VCS) cover a wide range of applications and consume large amounts of energy. In this context, previous research identified the optimization of the condenser fans speed as a promising measure to improve the energy efficiency of VCS. The present paper introduces a steady-state modeling approach of an air-cooled VCS to predict the ideal condenser fan speed. The model consists of a hybrid characterization of the main components of a VCS and the optimization problem is formulated as minimizing the total energy consumption by respectively adjusting the condenser fan and compressor speed. In contrast to optimization strategies found in the literature, the proposed model does not relay on algorithms, but provides a single optimization term to predict the ideal fan speed. A detailed experimental validation demonstrates the feasibility of the model approach and further suggests that the ideal condenser fan speed can be calculated with sufficient precision, assuming constant evaporating pressure, compressor efficiency, subcooling, and superheating, respectively. In addition, a control strategy based on the developed model is presented, which is able to drive the VCS to its optimal operation. Therefore, the study provides a crucial input for set-point optimization and steady-state modeling of air-cooled vapor compression systems.
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