Waste Heat Power Generation Using Low Thermal Resistance Thermoelectric Generators

Satoshi Someya･Hiroyasu Mino･Toshie Koyama (Tokyo Denki University)

To improve the thermal efficiency of vehicles with engines, such as hybrid vehicles, waste heat is converted into electricity using thermoelectric power generation devices. The system utilizes refrigerants for air conditioning as coolants to lower the temperature on the low-temperature side, while directing exhaust gases and high-temperature refrigerant flows to the high-temperature side. To maximize heat transfer through the thermoelectric power generation devices while keeping heat confined within the system, devices with low thermal resistance were fabricated and their power generation performance were evaluated.

Artificial Neural-Network Aided Model-Parameter Identification Method for Zero-Dimensional Heat Balance Model

Takeshi Miyamoto･Shuhei Takamura･Tatsuya Kuboyama･Yasuo Moriyoshi (Chiba University)

This study introduces a novel technique that utilizes an artificial neural network to identify the model parameters of zero-dimensional engine heat balance models. The method was demonstrated through the development of a model for a four-cylinder production gasoline engine.

Investigation of Heat Transfer Characteristics of a Plate Heat Exchanger for the Thermal Management System of a Hydrogen Fuel Cell Heavy-Duty Truck Using the Wilson Plot Method

Kee Young Yang･Yong Hyeon Park (Hyundai Motor)･Jun Hyuk Kim (Samsung Electronics)･Ho Seong Lee (Korea University)

Plate heat exchangers (PHEs) are essential for thermal management in hydrogen-electric heavy trucks, yet their automotive integration remains limited. Convective heat transfer coefficients for both fluid channels were quantified using a modified Wilson plot method under representative operating conditions. Analysis revealed an asymmetry, with the hot-side coefficient relatively lower than the cool side, constraining thermal efficiency. To address this, a multi-objective genetic algorithm was applied to optimize geometric parameters of offset-strip fin plates, including fin height, spacing, and strip length. The resulting designs significantly enhanced hot-side performance, offering a systematic approach for high-efficiency PHE configurations in fuel-cell vehicles.

A Study on the Improving Radiator Performance Prediction Accuracy to meet Cooling Target

Sangkyu Lee (Hyundai Motor)･Junjung Park (MPSE)

In the conceptual design phase, there often exists a significant discrepancy between the predicted data provided by suppliers and the actual test data for radiators. This issue primarily arises from the limitations of CAE analysis tools, which fail to adequately reflect the specific characteristics of radiators. To address this problem, we have developed a theoretical model that predicts performance based on actual test. Additionally, we have created a user-friendly program that enhances the accuracy and reliability of performance predictions by utilizing a dedicated database.

Development of Control Logic for Preventing Cooling Fan Motor Damage

Taewan Kim (Hyundai Motor)

Heavy rain concentrated during the monsoon season in South Asia is causing damage to cooling fan motors. Operating in a submerged state results in increased load on the cooling fan motor, leading to internal damage due to overload and ultimately causing the motor to fail. This results in engine overheating, and low performance of A/C. To resolve this issue, I aim to reduce field claims by implementing a logic system that detects flooding and restricts operation accordingly.