Model Of Thermal Management System Research Articles

Temperature management of liquid-cooled fuel cells based on active disturbance rejection control

In the proton exchange membrane fuel cell (PEMFC) systems, the operating temperature affects the gas transport, reaction rate and water balance inside the PEMFC stack, thus affecting the output performance and lifetime of the stack. Therefore, it is necessary to study the thermal management methods and control strategies to maintain the stack temperature at the expected value. A thermal management system model of the PEMFC based on the electrochemical reaction and thermodynamics is established. This study proposes a novel active disturbance rejection controller (ADRC) to solve the problem of excessive temperature fluctuation of liquid-cooled stack with the dynamic load current changes. The simulation data show that compared with the PID, Fuzzy-PID and PSO-PID controllers for the cooling fan, the overshoot amount of the coolant inlet temperature with the ADRC is significantly reduced from 1.02 %, 0.77 % and 0.26 % to 0.07 %, and the integral of time absolute error (ITAE) is decreased from 5.299 × 104, 5.206 × 104 and 1.255 × 104 to 3.930 × 103, respectively. The degree of temperature fluctuation is reduced and the parasitic power does not significantly increase. Therefore, the ADRC proposed in this study improves the temperature control effect of the PEMFC stack, which is conducive to enhancing the stack performance.

Analysis of cooperative cooling performance between the battery and cabin of pure electric vehicles

Abstract The cooperative cooling of the cabin and battery in pure electric vehicles (PEVs) is crucial for the comfort, thermal safety of the occupants, and the lifespan of the batteries. Therefore, a well-designed thermal management system (TMS) is particularly important. Thus, this paper constructs an cooperative cooling for the battery pack circuit and the cabin circuit in parallel, aiming to enhance the vehicle system’s integration and reduce energy consumption. Firstly, a one-dimensional simulation model of the cooperative TMS is established, and the model is calibrated through experiments. Subsequently, the system’s performance is analyzed under different ambient temperatures. The study finds that as the ambient temperature increases, the system’s energy consumption rises, and the Coefficient of Performance (COP) decreases. Moreover, when the system switches from the simultaneous cooling mode of the cabin and battery to the sole cooling mode of the cabin, the temperature of the cabin will fluctuate to a certain extent, within a range of 2°C. At same time, the COP value also increases with the switch of the mode. Finally, the analysis of the simultaneous cooling mode of the cabin and battery side under different ambient temperatures reveals that as the ambient temperature increases from 34°C to 42°C, the exhaust temperature, pressure ratio, and compressor speed increase accordingly, while the compressor efficiency decreases. The condenser and chiller experience a reduction in their heat transfer efficiency by 59.4 watts per degree Celsius and 218.5 watts per degree Celsius, respectively. Conversely, the evaporator’s heat transfer efficiency undergoes an enhancement of 6.77 watts per degree Celsius.

Modeling and control strategy optimization of battery pack thermal management system considering aging and temperature inconsistency for fast charging

Maintaining the battery pack’s temperature in the desired range is crucial for fulfilling the thermal management requirements of a battery pack during fast charging. Furthermore, the temperature difference, temperature gradient, aging loss and energy consumption of the battery pack should be balanced to optimize its performance. This paper establishes the liquid cooling thermal management system model for an electric vehicle’s battery pack, which accurately characterizes the temperature distribution and electrical and aging characteristics of the battery pack. The discrepancies between the experimental and simulated results of battery’s fast charging-cooling suggest that maximum absolute temperature error is 2 °C, and the maximum relative voltage error is 1.5 %. Based on the non-dominated sorting genetic algorithm II algorithm, an optimization model with aging and temperature gradient of cells as objective functions is established. Three different thermal management strategies are created according to the optimization results. The comparison of these thermal management methods with the constant temperature cooling strategy demonstrates that the minimum temperature gradient strategy enhances the temperature consistency of the battery pack and reduces the maximum temperature gradient by 27 %. The minimum aging thermal management strategy depicts an aging loss of 0.091 %, reducing the charging time by 272 s and the maximum temperature gradient by 2.0 °C. The balanced thermal management strategy enables the battery pack to balance the temperature gradient and aging loss by optimizing the charging time, battery pack temperature difference, energy consumption and other indicators. The weight of each indicator is determined by its information entropy, which can be replaced according to the diverse needs to achieve different balanced thermal management strategies, providing a reference for the actual application of thermal management strategies.

Research on the adaptability of energy management to thermal management of PEMFCs

Abstract The stable output of power and the effective control of stack temperature play a very important role in the durability and stability of fuel cell hybrid vehicles. In actual working conditions, energy management of power system and thermal management of Proton Exchange Membrane Fuel Cells (PEMFCs) need to be coordinated with each other to jointly ensure the efficient and stable operation of vehicles, however, most of the research in these two directions is independent. In response to the research gaps mentioned above, the concept of adaptability has been proposed for the first time with the aim of combining these two systems for research. This paper takes the fuel cell hybrid vehicle as the research object and establishes the energy management system and thermal management system model based on Matlab/Simulink software. In order to investigate the adaptability of energy management strategies to the temperature control system, two representative types of rule-based and optimization-based energy management strategies (power-following strategy, PFS, and adaptive equivalent hydrogen consumption minimization strategy, A-EHMS) are designed to be numerically simulated in the driving cycle condition of the UDDS, and then combined with the temperature control system of the fuel cell to comparatively analyze the above two types of energy management strategies from the perspectives of power allocation and the impact on the thermal management system. The results show that the PFS provides better protection for the battery under the same operating conditions. And from the perspective of fuel economy and adaptability to the temperature control system, the fuel consumption of A-EHMS is reduced by 12.5% and the adaptability to the temperature control system is improved by about 13.5% compared to PFS.

Modeling and simulating the thermal management system of a hydrogen fuel cell

Abstract Hydrogen energy is an important means of achieving decarbonization goals. Hydrogen fuel cells have broad application prospects due to their high-power output and wide temperature range. To improve the heat dissipation capacity of the fuel cell thermal management system, this paper establishes a simulation model of a 60kw fuel cell. The performance of the fuel cell engine thermal management system model under optimal operating parameters is studied by taking the temperature of the inlet and outlet water of the stack as the observation value. This is significant in improving the thermal environment of the fuel cell engine and ensuring its safe and efficient operation.

Thermal Management of Proton‐Exchange Membrane Fuel Cells with Enhanced Fuzzy Control via an Improved Whale Optimization Algorithm

Proton exchange membrane fuel cells (PEMFCs) require an appropriate operating temperature to achieve high performance and longevity. In addressing the critical need for effective thermal management in PEMFCs for vehicle propulsion systems, this study has developed and introduced a novel thermal management system model equipped with dual‐cooling loops. Addressing the issues of slow response and poor dynamic performance inherent in traditional control strategies, as well as the computational complexity that hinders the practical application of existing advanced control strategies, this research proposes a fuzzy proportional‐integral‐derivative (PID) controller optimizing the improved whale optimization algorithm (IWOA‐FPID) aimed at enhancing fan side control. By simulating step changes in current load and designing dynamic operating conditions based on the most basic and simple energy management system, the performance of IWOA‐FPID in temperature control is validated. The final results indicate that the IWOA‐FPID strategy significantly outperforms existing control methods, notably reducing adjustment time and minimizing temperature overshoot to ≈0.5 K. The proposed framework achieves efficient temperature control, highlighting its potential for broader application in vehicular fuel cells and offering a promising solution to the challenges of PEMFC thermal management.

Research on the thermal management safety of the fast charging power battery management system

In order to solve the problem of excessive heat generation in electric vehicle power batteries under extreme fast charging conditions, we have established a heat generation and thermal management system model for fast charging power batteries. The heat transfer efficiency of the power battery thermal management system under different environmental temperatures and experimental conditions was studied. The factors affecting the thermal management system of the power battery were analyzed by analyzing the speed and cooling capacity of the air conditioning compressor, the control parameters of the model and selecting the most suitable component configuration parameters by optimizing, a thermal management system has been designed to meet the cooling requirements of the power battery under different environmental temperatures and high-speed operating conditions. Through simulation and comparison of experimental data under different environmental temperatures, it is shown that the optimized fast charging power battery system can meet the design objectives under different environmental temperatures, and the battery temperature is always controlled within a reasonable temperature range. The designed power battery heat management system has good safety and robustness.

Control Strategy Analysis of Vehicle Thermal Management System Based on Motor Heat Utilization

Waste heat recovery can not only reduce the heating energy consumption during heating, but also assist the positive temperature coefficient to improve the heating efficiency. Herein, a motor waste heat recovery system composed of two four‐way valves is proposed. Through simulation and test, the thermal management system model is established based on the parameters of each component. Experiments and simulations are also conducted at 0, 20, and 40 °C. Under the New European Driving Cycle, it is verified that the motor waste heat recovery system can meet the heating demand of the cabin. At the same time, the temperature rise of the battery increases by 2.9% from 0 to 15 °C compared to no heat recovery system. From 0 to 18 °C, the cabin temperature increases by 8.1%. The cooling rate of the battery increases by 5.8% from 40 to 30 °C and the cooling rate of the cabin increases by 9.7% from 40 to 23 °C.

An integrated thermal management strategy for cabin and battery heating in range-extended electric vehicles under low-temperature conditions

The integrated thermal management strategy under low-temperature conditions can effectively alleviate mileage anxiety associated with electric vehicles and improve the thermal comfort of the cabin. In this study, an integrated thermal management topology for range-extended electric vehicles is proposed, which recovers the waste heat from the range extender and the electric drive system for the heating of the battery and the cabin to improve energy utilization. Considering the driving modes and heating demands, the working modes and switching rules are designed. Especially, a control-oriented coupling system model is established for pure-electric mode. Taking cabin heat load demand, battery heat generation, and electric drive system heat generation as disturbances, a model predictive controller is designed for the heating power of the heater. An integrated thermal management system model verified by experiments is established in AMEsim. The initial temperature of the environment and vehicle is −20 °C, and the target temperatures of the cabin and the battery are set at 20 °C and 25 °C respectively. The feasibility of the strategy is verified by the co-simulation of Simulink and AMEsim under 4 WLTC cycles. The results show that in the range-extended mode, the integrated system shortens the battery heating time and reduces fuel consumption by more than 10.2 % compared with the independent system. In pure-electric mode, the heating speed of the proposed model predictive control strategy is slightly faster than that of the on–off strategy, the heating energy consumption is reduced by 20.95 %, and the total energy consumption for propulsion and thermal management decreased by 2.84 %.

Modeling and simulation of vehicle integrated thermal management system for a fuel cell hybrid vehicle

The high-efficiency thermal management is one of the major challenges for fuel cell vehicles due to the diversity and complexity of the components and systems. Thermal management systems and corresponding control strategies can affect the components’ performance, durability and reliability, the vehicle’s driving performance, fuel economy and occupant thermal comfort. The main objective of this study is to perform multi-case simulation analysis of the fuel cell vehicle thermal management system through modeling to derive the operating mechanism and thermal performance analysis of each subsystem and integrated system. To achieve this purpose, an integrated thermal management system model with different control strategies was proposed based on a fuel cell vehicle prototype, powered by a 65 kW proton exchange membrane fuel cell stack and a Li-ion battery with a capacity of 15 kWh, which considers the cooling of the driving system, fuel cell stack, battery and cabin. The results showed that the critical temperature of each subsystem could be controlled within a reasonable range even in the battery charging mode, where the fuel cell generated about 136.6 % more thermal power than the discharging mode to charge the battery. Moreover, in the series structure of the radiators and condenser, the average temperatures of the inlet air of the motor and the subsequent fuel cell radiator were respectively 3.9 °C and 7 °C higher than the ambient temperature (35 °C), thus reducing the impact of the radiator fan. The proposed model may provide the contribution in the design of integrated solutions for thermal management systems for fuel cell hybrid vehicles under high temperature scenarios, including control strategies development and system-level coupling analysis.

An extreme gradient boosting-based thermal management strategy for proton exchange membrane fuel cell stacks

The working temperature is one of the critical factors for proton exchange membrane fuel cell (PEMFC) stacks, as it directly influences the performance and working life of PEMFCs. Due to the inherent nonlinearity of the PEMFC stack thermal management system model, current thermal management strategies (TMSs) generally face with the drawbacks of lower accuracy and robustness. In this research, a novel machine learning (ML) algorithm, i.e. the extreme gradient boosting (Xgboost) algorithm is applied to the TMS of a PEMFC stack to control the inlet and outlet temperatures of the PEMFC stack, where the proton exchange membrane (PEM) water content is also considered and kept at a reasonable level. In order to evaluate the effectiveness of the proposed strategy, a fuel cell hybrid vehicle (FCHV) model from Autonomie software is selected and the proposed TMS is tested and compared to other strategies under a mixed driving cycle for the PEMFC stack. Results show that the proposed Xgboost-based TMS presents the best control performance, which reduces the maximum deviation of the PEMFC stack temperature and the variation range of the PEM water content compared to other ML-based TMSs and the fuzzy logic-based TMS.

Control strategy research of electric vehicle thermal management system based on MGA-SVR algorithm

The thermal management system is one of the important assemblies that ensure the secure operation of electric vehicles (EVs). Using intelligent algorithms to optimize the control strategy of the thermal management system can reduce energy consumption under the premise of effective heat dissipation of EVs. This paper attempts to construct the control strategy of EV thermal management system by coupling the modified genetic algorithm (MGA) and support vector regression (SVR). Firstly, the double-population adaptive mutation method and a novel optimization process are adopted to obtain MGA. Afterward, the performance of MGA is verified by four benchmark functions compared with three typical algorithms, which are genetic algorithm (GA), double-population genetic algorithm (DPGA), and quantum genetic algorithm (QGA). The results demonstrate that the accuracy and stability of MGA are obviously better than the other three algorithms. Secondly, MGA is applied to modify parameters of SVR kernel function, and the accuracy of MGA-SVR algorithm is verified by the Auto-MPG and Computer Hardware data sets. The mean square deviations of the SVR algorithm test set are 0.0186 and 0.0806, respectively, and the mean square deviations of the MGA-SVR algorithm test set are 0.0099 and 0.0054, respectively, which fully shows that MGA-SVR have more accurate forecasting capabilities. Finally, the thermal management system model of EV is built by the one-dimensional simulation software KULI. Under the Chinese working condition, fan speed which meets the cooling requirements of the motor and controller is obtained from the KULI model, and the database is constructed. Then, MGA-SVR is trained by database and employed to predict fan speed under the Chinese working condition and obtain control strategy of the thermal management system. Compared with traditional control strategy, the thermal management system based on MGA-SVR control strategy can not only meet the radiating requirements, but also effectively reduce the power consumption of fans.

Research on performance of thermal management system for lithium-ion power battery

According to battery thermal management system’s design theory, a battery module with thermal management system is designed in this article, and the thermal management system model is simulated. By establishing thermal management system’s simulation model, modular thermal management system’s performance is analyzed.The simulation consequences show that the liquid cooling plate’s outlet temperature is higher than the inlet temperature, so the temperature rise and outlet temperature of the cooling liquid of a single battery module that cools system should be properly controlled. Through the thermal imager experiment, the test consequences are consonant with the simulation analysis’s conclusions.The reliability and accuracy of the simulation analysis is verified by the experiment, and shows the rationality of the design of the thermal management system for power battery.

Investigation on the performance enhancement of electric vehicle thermal management system utilizing floating loop with finite heat exchanger size

This study suggests an electric vehicle heat pump and thermal management system employing a floating loop. The floating loop manages the thermal state of power electronics and electric motors by utilizing the liquid refrigerant at the condenser outlet. This loop recovers the waste heat generated by power electronics and electric motors in winter and enhances the cooling performance in summer through the superior cooling performance of evaporative heat transfer. Configurations of heat pump and thermal management system are presented with operating schematic in summer and winter. To verify the performance of the suggested system, the heat pump and thermal management system model is established based on experimentally validated heat pump component models and electric device models. Heat exchangers are reallocated within a finite volume to investigate the effect of thermal load shift from the coolant to the refrigerant. The result shows that the heat pump system utilizing a floating loop with the largest refrigerant heat exchanger can save power consumptions in winter up to 27.7% and 5.8% in summer while maintaining the thermal state of electric devices within the appropriate range.

Data-driven reconstruction of interpretable model for air supply system of proton exchange membrane fuel cell

Appropriate air supply system controller is of great significance to improve the performance of proton exchange membrane fuel cell. Most of controllers rely on the high-precision, simple, and interpretable model. It is particularly important to establish the model for the fuel cell air supply system. Since the high-precision physically interpretable control-oriented model can provide an understanding of the underlying phenomena apart from computational tractability for aerodynamic problems. Data-driven sparse identification based on auto-encoder method is proposed to establish the model. It can be divided into the four steps. Firstly, collect data from a simulation model and the actual fuel cell system, and auto-encoder network is used to discover a coordinate transformation into a reduced space. Secondly, dictionary library is constructed from candidate terms based on system analysis. Thirdly, air supply model reconstruction problem is transformed into a sparse identification problem. Finally, the developed model is verified by two datasets. Compared with other methods, the results show that mean absolute error and root mean squared error of the three variables for proposed method are the smallest under both simulation data and real data. And the reconstruction results perfectly agree with the original simulation and the real data. Especially, the proposed method can be easily extended to other system modeling studies, such as the hydrogen supply system model and thermal management system model of the fuel cell system.

Analysis of Thermal Characteristics of Airborne Integrated Environmental Control System

Taking the simplified airborne integrated thermal management system as the research object, the change characteristics of the system under different control modes are analyzed, which provides a theoretical basis for the study of system control schemes. Using a combination of mathematical models and computer models to establish an integrated airborne thermal management system model with fuel as the main heat sink, air/fuel heat exchanger, fuel/PAO heat exchanger and other main components, and A fuzzy self-tuning PID control method is proposed to analyze system characteristics such as fuel/PAO heat exchanger and electronic equipment thermal changes. The results show that compared to open-loop control under thermal extreme conditions, the fuzzy self-tuning PID control mode can not only effectively control a series of equipment such as fuel pumps to maintain proper speed, but also ensure the electronic cabin and fuel/PAO heat exchanger the outlet temperature is kept within a predetermined range to meet the design requirements of the onboard thermal management system.

Performance Simulation Analysis of Composite Thermal Management System for Hypersonic Vehicle

A hybrid thermal management system model of hypersonic vehicle with liquid hydrogen as heat sink and thermoelectric conversion of Brayton cycle was established. The cooling effect, fuel flow demand and thermoelectric conversion characteristics of the thermal management system in flight envelope were studied by numerical simulation. The results show that the cooling fuel demand of refrigerant loop is about 0.22g/kW.s~0.24g/kW·s, that of aerothermal cooling fuel is about 0.11g/kW·s, and that of engine wall cooling fuel is about 0.08g/kW·s. The flow rate of engine wall cooling fuel can be saved by 25%∼40% during thermoelectric conversion. Thermoelectric conversion cycle efficiency and generation efficiency can reach up to 38% and 30%. When Mach number is 3.7∼4.2 under the condition of large aerodynamic heat load, the flow rate required for engine combustion is not enough to meet the cooling flow rate, and the maximum difference is 10%.

Electrochemical–Thermal Evaluation of an Integrated Thermal Management System for Lithium‐Ion Battery Modules

AbstractThermal management of lithium‐ion (Li‐ion) batteries using phase change materials (PCM) demonstrate advantages such as compactness and reduced weight compared to conventional active cooling systems. However, the heat accumulation in PCM due to ineffective cooling and added thermal inertia may lead to thermal management system failure. In this study, a hybrid active–passive thermal management system for a Li‐ion battery module is presented. Graphite nanopowder and highly oriented pyrolytic graphite sheets are employed to improve the low thermal conductivity of the PCM. The thermophysical properties of the nano‐enhanced PCM (NePCM) with various mass fractions are experimentally explored. A streamlined electrochemical–thermal coupled model for batteries is used to develop an air‐assisted hybrid thermal management system model. The effects of nanoparticles mass fraction, thickness of the PCM layer, and air inlet temperature on the module thermal behavior during a standard driving cycle are investigated. The hybrid system can maintain the module temperature within the safe limits and provide excellent temperature uniformity. The results reveal that an enhanced thermal conductivity is essential to recover the thermal energy storage capacity of PCM during the driving cycle. The proposed cooling approach presents a promising avenue for enhanced thermal management of Li‐ion battery modules.

Design and simulation of liquid cooled system for power battery of PHEV

Various battery chemistries have different responses to failure, but the most common failure mode of a cell under abusive conditions is the generation of heat and gas. To prevent battery thermal abuse, a battery thermal management system is essential. An excellent design of battery thermal management system can ensure that the battery is working at a suitable temperature and keeps the battery temperature diffenence at 2-3 °C. This paper presents a thermal-elcetric coupling model for a 37Ah lithium battery using AMESim. A liquid cooled system of hybrid electric vehicle power battery is designed to control the battery temperature.A liquid cooled model of thermal management system is built using AMESim, the simulation results showed that the temperature difference within 3°C of cell in the pack.

Integrated Aircraft Thermal Management System Modelling and Simulated Analysis

In order to improve the thermal energy utilization efficiency of aircraft, an integrated thermal management system model using endothermic fuel has been created in AMESIM. The system includes several thermal subsystems such as environment control system, the hydraulic equipment and power equipment cooling system, and anti-icing/de-icing system. The fuel oil was chosen for heat sink and it could cool the exothermic thermal system and transmit the energy to anti-icing/de-icing system in case of icing. Several simulation examples including three atmospheric conditions were accomplished. The results indicated that the present system had the ability to reuse the waste heat meanwhile all the thermal system worked normally. The anti-icing/de-icing didn’t need additional energy which realized less energy consumption. In addition, the model has the ability to facilitate the analysis and optimization of thermal systems on board.