Review of Thermal Management, Techno-Economic and Environmental Sustainability of photovoltaic Thermal Systems with Bibliometric

Potential applications of phase change materials for batteries' thermal management systems in electric vehicles

Assessment method of the integrated thermal management system for electric vehicles with related experimental validation

This chapter aims to describe the impact of vehicle electrification on the different thermal management systems. The first section of the chapter recalls the classification of hybrid and fully electric vehicles. The second section addresses the impact of electrification on the cabin climate control. Reversible heat pump systems are key components to cover both cabin cooling and heating loads, while limiting the vehicle driving range decrease. Different architectures of heat pumps, using different heat sources and heat sinks, are discussed. The last section covers battery thermal management as well as e-motors and power electronics cooling. Finally, the thermal management of the hybrid or electric vehicle as a whole is discussed. This last section aims at showing the benefit of integrating all thermal energy management systems in a way to increase the energy performance of the vehicle.

This research contributes to the goal of the cost reduction of vehicle electrification by addressing the thermal management of Lithium-Ion energy storage systems. Lithium-Ion secondary batteries are currently the state of the art for energy storage for vehicle electrification; however, to operate efficiently over their entire lifetime, these batteries must be held in their optimal temperature range. Concurrently, thermal management system cost must be minimized in order to guarantee the economic viability of vehicle electrification. To do so, novel thermal management concepts must be identified and compared to determine the ideal solution. This research presents a method for efficiently and reproducibly comparing diverse battery thermal management concepts in an early stage of development to assist in battery system design. The basis of this method is a hardware-based simulation model of a prismatic Lithium-Ion battery, called the Smart Battery Cell (SBC). The SBC models the thermal behavior of a prismatic automotive cell without the use of active chemistry. By removing the active chemistry, enhanced reproducibility of the experimental conditions is possible and hardware-in-the-loop integration can be realized, allowing for rapid reconditioning between experimental trials. The elimination of active chemistry reduces the safety risks associated with Lithium-Ion cells, making the use of the SBC possible with thermal management systems in an early state of developed, and without costly safety infrastructure. The integration of thermocouples leaves the thermal contact surface undisturbed, allowing the SBC to be integrated into diverse thermal management systems. Eight SBCs are combined to a reference module, as the cell module consisting of multiple cells is the current state of the art in battery system layout. By analyzing the thermal management concepts at module-level, the effects between cells can be observed (versus the analysis of a single cell), and the results from the module-level analysis can be scaled to different battery system sizes. The multifactorial analysis performed at module-level considers not only the thermal performance of the battery thermal management systems, but also the energy consumption, vehicle suitability, production complexity and economic viability. From the analysis, recommendations are made for the development of optimal thermal management systems to facilitate the cost reduction of vehicle electrification.

Experimental investigation of longevity and temperature of a lithium-ion battery cell using phase change material based battery thermal management system

Contemporary nano enhanced phase change materials: Classification and applications in thermal energy management systems

Lithium-ion batteries are widely adopted as portable energy storage devices due to their high energy capacity and relatively lightweight. Under high-intensity usage, an effective thermal management system is essential to control battery pack temperature within the desired range to guarantee battery safety and ensure a proper life cycle. This study developed a pulsating heat pipe (PHP) based thermal management system to promote battery temperature control. The system was tested for a large battery pack (2 kWh) under mild and severe ambient conditions via ANSYS Fluent simulation. A sensitivity study identified optimal PHP dimensions regarding the battery pack. The performance of PHP for both small and large scales was also evaluated. The system's effectiveness was compared to classical battery thermal management (BTM) systems such as forced air cooling, sidewall water cooling, and traditional heat pipes. The results demonstrated that the developed PHP-based passive cooling system effectively controls temperature, saves space, and reduces power consumption.

In the development and validation of complex systems such as energy management for Battery Electric Vehicles (BEVs), important figures are driving cycle patterns and the frequencies and durations in the change of environmental conditions. The change in the environmental conditions directly leads to the activiation and deactivation of event-chains to control the flow of energy and the conditioning of energy storage. Starting with the design of these systems, it would be beneficial to include also timing and the variance in timing of changing conditions. To reflect different occurrence rates, Markov modelling can be used. In system reliability engineering statistical Markov analysis is well understood. Recently, the three-dimensional Stochastic Markov chain modeling was published, which aims to optimize energy management by predicting driving behavior. However, all these approaches stick to the limitations of Continous Time Markov Chains (CTMC). The usage and change of conditions of thermal energy management systems in electric vehicles does not strictly obey the Markov properties. Overcoming the Markov properties, in this paper it is presented how various timing characteristics by using different propability functions can be used in modeling. With this, it is possible to model different occurrence types and durations of changing conditions, reflecting their type of frequency and distribution. With different types of modeling elements and a case study we demonstrate the modeling approach. The resulting model can be interpreted as a stochastic source for a Semi-Markov process. This allows for further analysis such as the derivation of indicators about reliability.

Liquid hydrogen storage, thermal management, and transfer-control system for integrated zero emission aviation (IZEA)

Due to the extreme sensitivity of temperature in Li‐ion batteries, thermal management is a significant issue that must be addressed. Since the battery in electric vehicles produces an enormous amount of heat, it reduces its efficiency and its performance. Currently, there is a need for electric vehicles (EVs) because conventional IC engines produce an enormous amount of pollution which affects the environment, so an electric vehicle produces a very small amount of pollution. It is now being recommended and used by many people. But the electric vehicle faces some major problems due to overheating in their battery module. Nowadays, battery temperature is regulated by a system called battery thermal management system (BTMS). Modern EVs use active and passive cooling systems. Thermal management tries to improve battery architecture for greater autonomy or quick charging. To meet future difficulties in thermal management, such as air or liquid cooling, are needed. As a result of the battery's overheating, the vehicle's performance, power, energy storage, charging, and discharging are all negatively impacted; hence, a reliable thermal management system for the battery is essential for resolving these problems. This study provides an overview of the BTMS of the future, beginning with the problems involving temperature and safety. The following is a list of the benefits and drawbacks of BTMSs, which are used to maintain acceptable temperatures for battery packs. In conclusion, an analysis of the progress made in developing temperature management systems for future batteries is presented. As a first look at potential BTMSs for locomotive applications, it has been proposed to conduct a comprehensive analysis and classification of both existing and potential battery management systems.

The lithium-ion battery is considered the primary power supply source for electric vehicles due to its high-energy density, long lifespan, and no memory effect. Its performance and safety highly depend on its operating temperature. Therefore, a battery thermal management system is necessary to ensure an electric vehicle (EV)’s performance. Air as a cooling medium is still used in a wide range of thermal management system applications, owing to its low-cost and lightweight. However, the conventional air-based cooling strategy shows an insufficient heat dissipation capacity and usually fails to block the thermal runaway propagation between batteries. Thus, it is of great importance for improving the heat dissipation of an air-based thermal management system. In this paper, three novel schemes (schemes B, C, and D) are introduced successively based on enhancing the heat transfer capacity and safety of a battery pack under a thermal runaway condition. Schemes B and C introduce a hollow spoiler prism and a spoiler prism filled with phase-change material with fins, respectively. The cooling effects of the three schemes are compared using computational fluid dynamics technology. The models of all the schemes are 3D symmetrical structures. In the CFD model, the battery heat-generating sub-model is incorporated through a user-defined function. The results indicate that all three schemes reduce the maximum temperature and the maximum temperature difference in the pack effectively compared with the conventional air cooling system. Scheme D presents the best cooling performance and hinders the propagation of the TR between adjacent batteries under a TR condition. The paper may provide a feasible method for improving the performance of an air-cooled thermal battery management system.

Experimental study on an air-based photovoltaic-thermal (PV-T) system with a converging thermal collector geometry: A comparative performance analysis

Recent progress in photovoltaic thermal phase change material technology: A review

Hybrid electric vehicles (HEVs) encounter the challenge of restricted versatility in harsh weather conditions, as the thermal management system (TMS) consumes noteworthy energy to control battery and cabin temperature. This paper proposes an economical thermal energy management system (eTEMS) and achieves multi-objective optimal control based on multiple agents deep reinforcement learning (DRL) algorithm. Firstly, a control-oriented coupled model of hybrid powertrain and TMS is designed to minimize energy loss. Secondly, the multiple agents deep deterministic policy gradient (DDPG) is formulated to attain cooperative optimization of fuel economy, battery lifespan preservation, and cabin thermal comfort. Moreover, centralized and decentralized training architecture is tailored to enhance the training efficiency and ensure the optimal performance. Finally, the real-time performance of proposed strategy is verified by Hardware-In-the-Loop (HIL). The results of HIL experiment indicate that the proposed strategy can reduce the vehicle driving costs in cold and hot environments by 13.28% and 7.1% respectively, while ensuring battery life and cabin thermal comfort. The real-time performance of proposed strategy is maintained at the millisecond level in HIL experiment, providing a comprehensive energy-saving solution for HEVs under diverse weather conditions.

A review on thermal management methods for robots