Cooling Air Temperature and Mass Flow Rate Control for Hybrid Electric Vehicle Battery Thermal Management

2014 ◽  
Author(s):  
Xinran (William) Tao ◽  
John Wagner
Keyword(s):  
Mass Flow Rate ◽  
Thermal Management ◽  
Air Temperature ◽  
Mass Flow ◽  
Flow Rate ◽  
Cooling System ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
Cooling Air

Lithium-Ion (Li-ion) batteries are widely used in electric and hybrid electric vehicles for energy storage. However, a Li-ion battery’s lifespan and performance is reduced if it’s overheated during operation. To maintain the battery’s temperature below established thresholds, the heat generated during charge/discharge must be removed and this requires an effective cooling system. This paper introduces a battery thermal management system (BTMS) based on a dynamic thermal-electric model of a cylindrical battery. The heat generation rate estimated by this model helps to actively control the air mass flow rate. A nonlinear back-stepping controller and a linear optimal controller are developed to identify the ideal cooling air temperature which stabilizes the battery core temperature. The simulation of two different operating scenarios and three control strategies has been conducted. Simulation results indicate that the proposed controllers can stabilize the battery core temperature with peak tracking errors smaller than 2.4°C by regulating the cooling air temperature and mass flow rate. Overall the controllers developed for the battery thermal management system show improvements in both temperature tracking and cooling system power conservation, in comparison to the classical controller. The next step in this study is to integrate these elements into a holistic cooling configuration with AC system compressor control to minimize the cooling power consumption.

Self-Adapting Intelligent Battery Thermal Management System via Artificial Neural Network Based Model Predictive Control

2019 ◽  
Author(s):  
Yuanzhi Liu ◽  
Jie Zhang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Model Predictive Control ◽  
Mass Flow Rate ◽  
Thermal Management ◽  
Predictive Control ◽  
Flow Rate ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System

Abstract This paper develops a self-adaptive control strategy for a newly-proposed J-type air-based battery thermal management system (BTMS) for electric vehicles (EVs). The structure of the J-type BTMS is first optimized through surrogate-based optimization in conjunction with computational fluid dynamics (CFD) simulations, with the aim of minimizing temperature rise and maximizing temperature uniformity. Based on the optimized J-type BTMS, an artificial neural network (ANN)-based model predictive control (MPC) strategy is set up to perform real-time control of mass flow rate and BTMS mode switch among J-, Z-, and U-mode. The ANN-based MCP strategy is tested with the Urban Dynamometer Driving Schedule (UDDS) driving cycle. With a genetic algorithm optimizer, the control system is able to optimize the mass flow rate by considering several steps ahead. The results show that the ANN-based MPC strategy is able to constrain the battery temperature difference within a narrow range, and to satisfy light-duty daily operations like the UDDS driving cycle for EVs.

scholarly journals Thermal Performance of a Cylindrical Lithium-Ion Battery Module Cooled by Two-Phase Refrigerant Circulation

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8094
Author(s):  
Bichao Lin ◽  
Jiwen Cen ◽  
Fangming Jiang
Keyword(s):  
Thermal Management ◽  
Management System ◽  
Cooling System ◽  
Maximum Temperature ◽  
Two Phase ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
Li Ion ◽  
Battery Module

It is important for the safety and good performance of a Li-ion battery module/pack to have an efficient thermal management system. In this paper, a battery thermal management system with a two-phase refrigerant circulated by a pump was developed. A battery module consisting of 240 18650-type Li-ion batteries was fabricated based on a finned-tube heat-exchanger structure. This structural design offers the potential to reduce the weight of the battery thermal management system. The cooling performance of the battery module was experimentally studied under different charge/discharge C-rates and with different refrigerant circulation pump operation frequencies. The results demonstrated the effectiveness of the cooling system. It was found that the refrigerant-based battery thermal management system could maintain the battery module maximum temperature under 38 °C and the temperature non-uniformity within 2.5 °C for the various operation conditions considered. The experimental results with 0.5 C charging and a US06 drive cycle showed that the thermal management system could reduce the maximum temperature difference in the battery module from an initial value of 4.5 °C to 2.6 °C, and from the initial 1.3 °C to 1.1 °C, respectively. In addition, the variable pump frequency mode was found to be effective at controlling the battery module, functioning at a desirable constant temperature and at the same time minimizing the pump work consumption.

scholarly journals Experimental Investigation on a Thermoelectric Cooler for Thermal Management of a Lithium-Ion Battery Module

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xinxi Li ◽  
Zhaoda Zhong ◽  
Jinghai Luo ◽  
Ziyuan Wang ◽  
Weizhong Yuan ◽  
...  
Keyword(s):  
Thermal Management ◽  
Cooling System ◽  
Discharge Rate ◽  
Lithium Ion ◽  
Design And Optimization ◽  
System A ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
Battery Module

Electric vehicles (EVs) powered by lithium batteries, which are a promising type of green transportation, have attracted much attention in recent years. In this study, a thermoelectric generator (TEG) coupled with forced convection (F-C) was designed as an effective and feasible cooling system for a battery thermal management system. A comparison of natural convection cooling, F-C cooling, and TEG cooling reveals that the TEG is the best cooling system. Specifically, this system can decrease the temperature by 16.44% at the discharge rate of 3C. The coupled TEG and F-C cooling system can significantly control temperature at a relatively high discharge rate. This system not only can decrease the temperature of the battery module promptly but also can reduce the energy consumption compared with the two other TEG-based cooling systems. These results are expected to supply an effective basis of the design and optimization of battery thermal management systems to improve the reliability and safety performance of EVs.

scholarly journals Investigation of the Applicability of Helium-Based Cooling System for Li-Ion Batteries

Electrochem ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 135-148
Author(s):  
Mohammad Alipour ◽  
Aliakbar Hassanpouryouzband ◽  
Riza Kizilel
Keyword(s):  
Thermal Management ◽  
Cooling System ◽  
Flow Direction ◽  
Maximum Temperature ◽  
Li Ion Batteries ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Inlet Flow Rate ◽  
Battery Thermal Management System ◽  
Li Ion

This paper proposes a novel He-based cooling system for the Li-ion batteries (LIBs) used in electric vehicles (EVs) and hybrid electric vehicles (HEVs). The proposed system offers a novel alternative battery thermal management system with promising properties in terms of safety, simplicity, and efficiency. A 3D multilayer coupled electrochemical-thermal model is used to simulate the thermal behavior of the 20 Ah LiFePO4 (LFP) cells. Based on the results, He gas, compared to air, effectively diminishes the maximum temperature rise and temperature gradient on the cell surface and offers a viable option for the thermal management of Li-ion batteries. For instance, in comparison with air, He gas offers 1.18 and 2.29 °C better cooling at flow rates of 2.5 and 7.5 L/min, respectively. The cooling design is optimized in terms of the battery’s temperature uniformity and the battery’s maximum temperature. In this regard, the effects of various parameters such as inlet diameter, flow direction, and inlet flow rate are investigated. The inlet flow rate has a more evident influence on the cooling efficiency than inlet/outlet diameter and flow direction. The possibility of using helium as a cooling fluid is shown to open new doors in the subject matter of an effective battery thermal management system.

Development of a heat pipe–based battery thermal management system for hybrid electric vehicles

2020 ◽  
Vol 234 (6) ◽  
pp. 1532-1543
Author(s):  
Junkui (Allen) Huang ◽  
Shervin Shoai Naini ◽  
Richard Miller ◽  
Denise Rizzo ◽  
Katie Sebeck ◽  
...  
Keyword(s):  
Thermal Management ◽  
Core Temperature ◽  
System Performance ◽  
Management System ◽  
Cooling System ◽  
Battery Pack ◽  
Ambient Conditions ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System

Enhanced battery pack cooling remains an open thermal management challenge in hybrid electric vehicle applications. A robust cooling system should maintain the battery pack core temperature within a prescribed operating range to improve system performance, durability, and reliability while minimizing power consumption. This paper proposes a smart battery thermal management system utilizing heat pipes as a thermal bus to efficiently remove heat. The system couples a standard air conditioning system with traditional ambient air ventilation. The two loops can run independently or in tandem to achieve the desired control. A nonlinear model predictive controller was developed to maintain the battery core temperature within a designated range using the compressor and fan speeds as the control inputs. A mathematical battery thermal model was developed to estimate the core and surface temperatures. The system performance and power requirements were evaluated for various driving cycles and ambient conditions. Numerical results showed that the proposed cooling system can regulate the battery core temperature within the desired temperature range (maximum tracking error of 2.1°C) while compensating for ambient temperature conditions using a suitable cooling strategy. The simulation results showed the ability to remove up to 1135 kJ of heat. The simulation also presents the power consumed by system components under varying modes and ambient conditions.

Parameter Study on Cooling System of Battery for HEV

2012 ◽  
Vol 538-541 ◽  
pp. 2038-2042
Author(s):  
Zhen Zhe Li ◽  
Yun De Shen ◽  
Gui Ying Shen ◽  
Mei Qin Li ◽  
Ming Ren
Keyword(s):  
Heat Flux ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Cooling System ◽  
Parameter Study ◽  
Analysis Model ◽  
Rate Of Cooling ◽  
Future Work ◽  
Cooling Air

A hybrid power composed of the fuel cell and MH-Ni battery has become a good strategy for HEV, but the performance of the battery cooling systems can not be easily adjusted. In this study, heat flux of the batteries and mass flow rate of cooling air have been investigated to improve the performance of a battery cooling system. As shown in the results, the error of root mean square has been decreased under the condition of decreasing heat flux of the batteries, and the performance of the battery cooling system has been improved with increasing the mass flow rate of cooling air. The analysis model developed in this study can be widly used to find out an optimal battery cooling system in the future work.

Performance Evaluation of Battery Thermal Management System in Electric Vehicle using Induction Heater (Part 1: Parallel System)

2020 ◽  
Vol 28 (01) ◽  
pp. 2050003
Author(s):  
Waseem Raza ◽  
Gwang Soo Ko ◽  
Youn Cheol Park
Keyword(s):  
Heating Rate ◽  
Thermal Management ◽  
Flow Rate ◽  
Management System ◽  
Parallel System ◽  
Working Fluid ◽  
Induction Heater ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System

The fast evolving Electric vehicles (EVs) have become popular due to their zero-emission, fuel economy and better technology. However, the performance and life of batteries are very sensitive to temperature, it is important to maintain the proper temperature range. The battery thermal management system (BTMS) plays an important role in the performance of EVs. In this context, this study is conducted to evaluate the thermal performance of a battery with a parallel system using an induction heater. The GT-Suite software is used for simulation and evaluation. Mixture of water and ethylene glycol 50:50 is used as a working fluid and controlled by pump and valves. The heating rate of battery was analyzed by changing the capacity of induction heater 2, 4 and 6[Formula: see text]kW and the flow rate of fluid was 2, 3, 5, 7, 10 and 27 LPM. The simulation work predicts that the battery heating rate increases with the increase in fluid flow. The study concluded that the battery heating rate is maximum with a flow rate of 27 LPM which is the highest amount of LPM, indicating that the rise in flow rate causes the increase in heating rate of the system which is also affected by induction heater capacity.

Influence of temperature and volume fraction on the thermophysical properties of CuO-R134a nano refrigerant and its application in battery thermal management system

2021 ◽  
pp. 095440892110158
Author(s):  
S Senthilraja ◽  
P Ravichandran ◽  
R Gangadevi
Keyword(s):  
Heat Transfer ◽  
Thermal Management ◽  
Thermophysical Properties ◽  
Management System ◽  
Cooling System ◽  
Average Cell ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
The Impact

The battery temperature is one of the important factor that affects the performance of the battery and lifetime. To overcome these issues, the need and usage of an effective battery thermal management system (BTMS) is increased in recent years. The results of BTMS with conventional heat transfer fluids appears in many articles but the very few researchers developed and studied the performance of refrigerant based BTMS. In this research, a novel BTMS is developed and detailed study is conducted to analyze the impact of CuO based refrigerant (R134a) on its performance. Different quantity of CuO nanoparticles mixed with base refrigerant (R134a) and used as a heat transfer fluid. Initially, five different volume proportions (i.e. ɸ – 0.01, 0.02, 0.03, 0.04 and 0.05%) of CuO-R134a nano refrigerants are prepared and the thermophysical properties are studied. The test results reveal that the peak thermal conductivity and viscosity of about 1.28 W/mK and 0.00047 Pa-S is obtained for refrigerant with 0.05 vol.% CuO nanoparticle at 325 K and 300 K respectively. The average cell temperature of about 51 °C, 37 °C, 33 °C and 32 °C is observed for battery without cooling system, BTMS with R134a, 0.01% and 0.05% CuO/R134a respectively. From the results of this study, it can be suggested that the CuO- R134a nano refrigerant will be a promising cooling medium in the battery cooling system.

An Experimental Parametric Study of Air-Based Battery Thermal Management System for Electric Vehicles

2017 ◽  
Author(s):  
Yuanzhi Liu ◽  
Mao Li ◽  
Jie Zhang
Keyword(s):  
Thermal Management ◽  
Electric Vehicles ◽  
Thermal Performance ◽  
Maximum Temperature ◽  
Design Parameters ◽  
Experimental Platform ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
Cooling Air

This paper develops an experimental platform and performs a parametric study of an air-based battery thermal management system (BTMS) for electric vehicles. A flexible experimental platform with ten battery cells is built up to investigate how key BTMS design parameters affect the battery thermal performance. Three design parameters are studied in this paper, including the mass flow rate of cooling air, the heat flux from the battery cells to the cooling air, and the passage spacing size. To evaluate the thermal performance of the battery system, two metrics (i.e., the maximum temperature rise and the maximum temperature Uniformity) are used. A design of experiments (here 30 groups) are conducted to analyze how the three key design parameters affect the thermal performance of the BTMS. A computational fluid dynamics (CFD) of the BTMS is also performed to compare and help explain the experimental results. Both the experimental and CFD simulation results shows that: (i) decreasing the mass flow rate may deteriorate the thermal performance of the battery module; (ii) increasing the heat flux and enlarging the passage spacing size also deteriorate the battery thermal performance.

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