Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins

Vehicle climate control systems aim to keep passengers thermally comfortable. However, current systems control temperature rather than thermal comfort and tend to be energy hungry, which is of particular concern when considering electric vehicles. This paper poses energy-efficient vehicle comfort control as a Markov Decision Process, which is then solved numerically using Sarsa({\lambda}) and an empirically validated, single-zone, 1D thermal model of the cabin. The resulting controller was tested in simulation using 200 randomly selected scenarios and found to exceed the performance of bang-bang, proportional, simple fuzzy logic, and commercial controllers with 23%, 43%, 40%, 56% increase, respectively. Compared to the next best performing controller, energy consumption is reduced by 13% while the proportion of time spent thermally comfortable is increased by 23%. These results indicate that this is a viable approach that promises to translate into substantial comfort and energy improvements in the car

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model

Review of Cabin Thermal Management for Electrified Passenger Vehicles

Peer reviewe

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 133)

This special bibliography lists 276 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in September 1974

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 145

This bibliography lists 301 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1975

Suited for spacewalking: A teacher's guide with activities

This publication is an activity guide for teachers on spacesuits and spacewalking. It uses the intensive interest many children have in space exploration as a launching point for hands-on-opportunities. The guide begins with brief discussions of the space environment, the history of space walking, the Space Shuttle spacesuit, and working in space. These are followed by a series of activities that enable children to explore the space environment as well as the science and technology behind the functions of spacesuits. The activities are not rated for specific grade levels because they can be adapted for students of many ages. The guide concludes with a brief glossary as well as references and resources

The condition of challenge : a tool for experiential design

The experience of challenge in the natural environment provides opportunities for achievement that lead to psychological growth such as increased self esteem. This inquiry addresses the potential role of environmental challenge and comfort in environments de signed to facilitate psychological growth and learning. By studying physical, psychological, and sensory experiences of challenge in a landscape, it may be possible to incorporate similar physical, psychological, and sensory experiences into man-made interventions in the same landscape strengthening the potential support for psychological growth and learning in the total experience of environment

J Occup Environ Hyg

The international fire service community is actively engaged in a wide range of activities focused on development, testing, and implementation of effective approaches to reduce exposure to contaminants and the related cancer risk. However, these activities are often viewed independent of each other and in the absence of the larger overall effort of occupational health risk mitigation. This narrative review synthesizes the current research on fire service contamination control in the context of the National Institute for Occupational Safety and Health (NIOSH) Hierarchy of Controls, a framework that supports decision making around implementing feasible and effective control solutions in occupational settings. Using this approach, we identify evidence-based measures that have been investigated and that can be implemented to protect firefighters during an emergency response, in the fire apparatus and at the fire station, and identify several knowledge gaps that remain. While a great deal of research and development has been focused on improving personal protective equipment for the various risks faced by the fire service, these measures are considered less effective. Administrative and engineering controls that can be used during and after the firefight have also received increased research interest in recent years. However, less research and development have been focused on higher level control measures such as engineering, substitution, and elimination, which may be the most effective, but are challenging to implement. A comprehensive approach that considers each level of control and how it can be implemented, and that is mindful of the need to balance contamination risk reduction against the fire service mission to save lives and protect property, is likely to be the most effective.CC999999/Intramural CDC HHSUnited States