This blog post is a summary of a technical webinar presented in conjunction with Gamma Technologies for SAE Tech Briefs.

Increasing electrification of the automotive industry presents significant challenges for OEMs prioritizing human comfort and for engineers designing efficient heating and cooling systems. Unlike internal combustion engine vehicles, electric vehicles (EVs) cannot utilize waste heat from the engine; thus, expending energy to condition the cabin is a direct drain on the vehicle's range. Studies indicate a drastic 50-70% range reduction in cold conditions, with cabin heating accounting for nearly 40% of that reduction.

Traditional HVAC systems predominantly rely on bulk environmental metrics, such as Predicted Mean Vote (PMV), to regulate the cabin climate. While these metrics offer a general indication of thermal comfort for a hypothetical average occupant, they often fail to address individual preferences and can lead to energy inefficiencies in EVs by uniformly conditioning the entire cabin space. 

In contrast to conventional central HVAC systems that condition the entire cabin volume, microclimate devices, such as climate-controlled seats, heated steering wheels, and neck warmers, directly interact with and condition the occupant. This targeted approach offers the potential for significantly improved time-to-comfort while simultaneously enhancing energy efficiency. 

This blog post outlines a technical workflow for designing a human-centric auto-climate control system. It leverages a physiology-based human thermal comfort model, specifically the Berkeley model, to optimize individual comfort and energy efficiency through targeted microclimate control. 

Key Inputs for Designing an Advanced Microclimate System with Local Comfort Effectors 

Physiological Approach Using the Berkeley Thermal Comfort Model

The Berkeley thermal comfort model offers a significant leap forward by simulating the human thermoregulatory system in detail. Instead of treating the human body as a single entity, it divides it into 19 distinct segments, calculating the skin and core temperatures for each based on the surrounding thermal boundary conditions. This granular approach allows for the determination of local thermal sensation and comfort for each segment, which are then aggregated to provide an overall sensation/comfort assessment. 

A key advantage of the Berkeley model in the cabin comfort context is its ability to account for alliesthesia, a phenomenon where a very positive localized comfort in certain body parts can compensate for less optimal overall thermal sensation. Imagine the transition to a hot tub or sauna directly after a polar plunge. This degree of comfort can only be achieved by achieving a highly positive ‘opposite sensation’. This phenomenon is crucial for understanding how targeted microclimate interventions can improve overall comfort even if bulk environmental conditions remain sub-optimal. The model operates on a nine-point scale, ranging from -4 (very cold) to +4 (very hot), providing a detailed assessment of thermal experience. 

Targeting Local Comfort with Microclimate Effectors  

To capitalize on the detailed insights provided by the Berkeley model, this approach investigates the use of specific microclimate devices designed to influence the thermal environment of individual body segments. The study explored both warm-up and cool-down scenarios to assess the benefits of the integrated system under different conditions. The local comfort effectors simulated include: 

• Heating: Neck warmer, heated seat, heated armrest, heated steering wheel. 

• Cooling: Neck conditioner, cooled seat, cooled steering wheel. 

The underlying principle is to provide localized heating or cooling precisely where it is needed, enhancing comfort for specific body parts while supplying less conditioning to the cabin air.

Intelligent Control for Efficient Operation  

The control scheme for these microclimate devices is designed to maximize efficiency and mimic individual adjustments from the occupants. The core strategy involves targeting peak local comfort for each body segment directly influenced by a particular device. For example, the seatback heat rate is controlled to optimize the local comfort of the back segment. This targeted approach minimizes the energy required to operate each device while maximizing its impact on individual comfort. Furthermore, the control system incorporates touch temperature limitations for devices like heated steering wheels to adhere to safety constraints.  

Virtual Testing Methodology: Model-in-the-Loop Simulation  

To evaluate the effectiveness of this approach, a virtual testing procedure was implemented pairing Gamma Technology’s GT-SUITE and ThermoAnalytics’ TAITherm in a co-simulation workflow. This study compared a traditional HVAC system alone against a next-gen HVAC + microclimate system, in which the HVAC system was targeting a less aggressive temperature setpoint.

The co-simulation methodology utilized GT-SUITE's coupling capabilities to enable real-time signal exchange between the Berkeley thermal comfort model and the controllers managing the microclimate devices. This "model-in-the-loop" approach allows for dynamic adjustments based on the simulated human thermal response. 

Results 

Warm-up Scenario: 

• The heated seat demonstrated a significant improvement in local comfort (25-35%) for the back, pelvis, and legs, highlighting its effectiveness in providing targeted warmth. 
  
  
• The heated armrest also showed substantial local comfort gains (30-50%) for the forearm, indicating its potential for enhancing upper body comfort. 
  
  
• The heated steering wheel provided a smaller but still noticeable improvement in comfort (20-35%). The touch temperature limitations prevented it from becoming too hot, thus limiting the potential for greater comfort enhancement. 
  
  
• The neck warmer showed minimal impact on local comfort (<7%), suggesting a potential design issue, most likely related to low airflow or insufficient heating capacity. 
  
  
• Overall, the microclimate system achieved a >10% reduction in energy consumption compared to HVAC alone while simultaneously providing a 3-8% improvement in overall comfort as predicted by the Berkeley model. This starkly contrasts with the PMV, which indicated a lower comfort level with the microclimate system, underscoring the limitations of bulk metrics in evaluating localized interventions. 
  
  
  

Cool-down Scenario: 

• The cooled seat and steering wheel accelerated the cooling process for their respective contact areas. However, their overall effectiveness of the seat was limited as the HVAC system alone was relatively efficient in this scenario. 
  
  
• Overall, the energy reduction in the cool-down scenario was negligible, and the overall comfort, as assessed by the Berkeley model, was slightly worse. This suggests potential for overcooling in localized areas when microclimate devices are used in conjunction with an already effective HVAC system. 
  
  

Conclusions and Future Directions 

This study demonstrates the significant potential of utilizing physiology-based human thermal comfort models in ThermoAnalytics’ TAITherm to guide the development and control of microclimate systems. The virtual climate system model proved to be an effective tool for "model-in-the-loop" testing, enabling the evaluation of complex interactions between the human body, microclimate devices, and the cabin environment. 

The key takeaways from this study include: 

• Targeting peak local comfort with microclimate effectors can significantly improve individual comfort and reduce energy consumption, particularly in warm-up scenarios.  

• Physiology-based models are essential for accurately evaluating the benefits of localized comfort interventions. Traditional bulk metrics like PMV can be misleading and fail to capture the nuances of individual thermal experience. 

• More comprehensive microclimate systems with a greater number of strategically placed devices have the potential for even greater energy efficiency improvements. Expanding the array of local comfort effectors could provide additional influence over individual thermal comfort. 

• Device sizing and control strategies are critical for optimizing performance. Factors like airflow for convention-based devices need careful consideration to maximize their impact. 

This research underscores the transformative potential of microclimate technology, guided by advanced thermal comfort models, in creating more comfortable and energy-efficient climate control systems. Future work should focus on refining device designs, developing more sophisticated control algorithms, and exploring the integration of individual comfort preferences into the control strategy to further personalize the thermal experience and minimize energy demand. By moving beyond the limitations of bulk environmental metrics, we can pave the way for truly occupant-centric and sustainable climate control solutions. 

About the Author

Deniz Hinz, PH.D. is a Senior Thermal and CFD Engineer at ThermoAnalytics Inc., where he leads the development and validation of advanced cabin simulation methodologies. Deniz specializes in coupling 1D and 3D solvers with human thermal comfort modeling to create integrated multiphysics simulation workflows for cabin environments. Recognized for his meticulous approach and innovative problem solving, he delivers solutions that are both highly accurate and tailored to client-specific needs. Deniz holds a BSE in Chemical Engineering from the University of Michigan and a PhD from the Illinois Institute of Technology, where his research centered on CFD model development and validation for complex, multiphase flows.