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Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

Traditional vehicle air conditioning systems condition the entire cabin to a comfortable range of temperature and humidity regardless of the number of passengers in the vehicle. The A/C system is designed to have enough capacity to provide comfort for transient periods when cooling down a soaked car. Similarly for heating, the entire cabin is typically warmed up to achieve comfort. Localized heating and cooling, on the other hand, focuses on keeping the passenger comfortable by forming a micro climate around the passenger. This is more energy efficient since the system only needs to cool the person instead of the entire cabin space and cabin thermal mass. It also provides accelerated comfort for the passenger during the cooling down periods of soaked cars. Additionally, the system adapts to the number of passengers in the car, so as to not purposely condition areas that are not occupied.

The focus of this study is to validate the predictive capability of a recently developed physiology based thermal comfort modeling tool in a realistic thermal environment of a vehicle passenger compartment. Human subject test data for thermal sensation and comfort was obtained in a climatic wind tunnel for a cross-over vehicle in a relatively warm thermal environment including solar load. A CFD/thermal model that simulates the vehicle operating conditions in the tunnel, is used to provide the necessary inputs required by the stand-alone thermal comfort tool. Comparison of the local and the overall thermal sensation and comfort levels between the human subject test and the tool's predictions shows a reasonably good agreement. The next step is to use this modeling technique in designing and developing energy-efficient HVAC systems without compromising thermal comfort of the vehicle occupants.

Virtual simulation of passenger compartment climatic conditions is becoming increasingly important as a complement to the wind tunnel and field testing to achieve improved thermal comfort while reducing the vehicle development time and cost. The vehicle cabin is subjected to various thermal environments. At the same time many of the design parameters are dependent on each other and the relationship among them is quite complex. Therefore, an experimental parametric study is very time consuming. The present 3-D RadTherm analysis coupled with the 3-D CFD flow field analysis takes into account the geometrical configuration of the passenger compartment which includes glazing surfaces and pertinent physical and thermal properties of the enclosure with particular emphasis on the glass properties. Virtual Thermal Comfort Engineering (VTCE) is a process that takes into account the cabin thermal environment coupled with a human physiology model.

Simulation of cabin climatic conditions is becoming increasingly important as a complement to wind tunnel and field testing to help achieve improved thermal comfort while reducing vehicle development time and cost. Delphi developed the Virtual Thermal Comfort Engineering (VTCE) process to explore different climate control strategies as they relate to occupant thermal comfort in a quick and inexpensive manner. The comfort model has the ability to predict the local thermal comfort level of an occupant in a highly non-uniform thermal environment as a function of air temperature, surrounding surface temperatures, air velocity, humidity, direct solar flux, as well as the level of activity and clothing type of each individual.

Delphi Harrison Thermal System's comfort model can be used to predict the local thermal comfort level of an occupant in the highly non-uniform thermal environment of a vehicle cabin. This model is based on the concept of Equivalent Homogeneous Temperature (EHT) to assess the local comfort of 16 body segments as a function of air temperature, surrounding surface temperatures, air velocity, humidity, direct solar flux, as well as the level of activity and clothing type of each individual. Although EHT has been accepted by some European automotive industries, OEMs in North America have their own comfort scales. In the present study, we developed a model to correlate our EHT scale to an OEM's comfort scale. The current comfort model based on EHT produced excellent agreements with human subject data based on an OEM's comfort scale for both summer and winter rides.

An ultrasonic air temperature sensor, intended to help improve automatic climate control (ACC), has been demonstrated in a vehicle. Ideally, ACC should be based on inputs correlated with thermal comfort. Current ACC systems do not measure the air temperature best correlated to thermal comfort - at breath level in front of an occupant. This limits the thermal comfort that ACC can provide under transient conditions. An ultrasonic sensor measures the bulk air temperature, is transparent to the driver, and can use commercially available components. In a proof-of-concept test, we monitored the thermal transients in a vehicle during cool-down after a hot soak and also during warm-up after a cold soak. The ultrasonic path was along the roof console. The ultrasonic temperature always agreed to ±1 °C with the air temperature measured by a thermocouple at the midpoint of the ultrasonic path.

Automatic climate control could be improved by measuring air temperature ultrasonically. Thermal comfort correlates better with bulk air temperature than with the temperature measured by the in-car sensor. The time of flight of an ultrasonic pulse through the air gives the bulk air temperature. In a proof-of-concept experiment, it is accurate to ± 0.5 °C from -40 to+60 °C. Two operational modes are demonstrated: pulse-echo in which a single transducer creates a pulse and detects its return from a reflector, and single-pass in which a source transducer creates a pulse that travels directly to a separate transducer.

Simulation of passenger compartment climatic conditions is becoming increasingly important as a complement to wind tunnel and field testing to help achieve improved thermal comfort while reducing vehicle development time and cost. Delphi Harrison Thermal Systems has collaborated with the University of California, Berkeley to develop the capability of predicting occupant thermal comfort to support automotive climate control systems. At the core of this Virtual Thermal Comfort Engineering (VTCE) technique is a model of the human thermal regulatory system based on Stolwijk’s model but with several enhancements. Our model uses 16 body segments and each segment is modeled as four body layers (core, muscle, fat, and skin tissues) and a clothing layer.

Three-dimensional flow and temperature distributions in a passenger compartment are very important for evaluating passenger comfort and improving A/C system design. In the present study, the Reynolds-averaged Navier-Stokes equations and the energy transport equation were solved, by both quasi-steady and full transient approaches, to simulate a passenger compartment cooling process. By comparing the predictions with experimental results for a simplified GM-10 passenger compartment, the accuracy of the simulation was assessed. Throughout the 800-second period, good agreement was observed between the measured breath-level air temperatures and the prediction of the transient simulation. The quasi-steady simulation underpredicted air temperatures at the very early stage of the cooling process. However, after 200 seconds of cool down, the quasi-steady simulation predicted air temperatures equally as well as the full transient simulation.