Flow Resistance Network Research Articles

The integrated multi-performance fast optimization strategy for battery thermal management system

Increased battery energy density is required to boost electric vehicle endurance; however, this also raises the possibility of thermal runaway and power battery explosion. Improving the cooling system performance requires optimization and enhancement of classical systems. Traditional design approaches struggle to simultaneously enhance multiple aspects of performance, while an optimization based on Computational Fluid Dynamics (CFD) methods is often inefficient. Therefore, by integrating a flow resistance network model (FRNM) with a weighted average optimization algorithm (INFO), an efficient optimization for the comprehensive performance of the system can be achieved. Five optimized systems under different airflow rates were obtained through optimization. A comparison with two existing systems validated the effectiveness of the optimized system. The results demonstrate that, compared to the two reference systems, the optimized system decreases the maximum temperature difference by 65.51 % and 39.07 %, respectively. Furthermore, the improvement in temperature uniformity is more significant, increasing by 63.76 % and 34.40 %, respectively.

Numerical modelling and analysis of porous surface-enhanced jet cooling using copper inverse opals in single-phase flow

Abstract In this study, we propose a novel cooling scheme that utilizes copper inverse opals (CIOs) for surface enhancement in a single-phase impingement jet cooling system. We perform computational fluid dynamics simulations to evaluate the cooling performance of the CIO jet coolers. Our modelling results indicate that the proposed CIO-coated cooler can significantly reduce the average temperature and improve the temperature uniformity across the entire chip surface. The average Nusselt number of the CIO-coated cooler can reach up to 2.8 times that of the flat surface jet cooler. However, the porous structure of the CIO-coated cooler increases the total pressure drop. To determine designs with high cooling performance and low energy consumption, we investigate two crucial design factors, namely the inlet velocity and the nozzle-to-CIO distance. Our analysis reveals that increasing the inlet velocity further enhances the heat transfer, but at the expense of high pressure drop. On the other hand, a larger nozzle-to-CIO distance results in a lower pressure drop but also reduces the heat transfer coefficient. The effects of nozzle-to-CIO distance are further understood by studying the flow resistance network. Furthermore, we present a reduced-order model that accurately captures the thermofluidic characteristics of the proposed design.

Numerical and experimental study on efficient optimization of variable cross-section battery thermal management systems using an improved flow resistance network model

Air-cooled systems are widely used for cooling of battery packs in electric vehicles. Optimization method combined with the flow resistance network (FRN) model is effective for system design. However, the local pressure loss of divergence and convergence ducts in the traditional FRN model is ignored, leading to large error when applying the model in systems with variable cross-section channels. In this study, the local loss coefficients of the contractive and diffusive channels are derived and the improved FRN model is developed for velocity calculation of variable cross-section air-cooled systems. The improved model is verified using computational fluid dynamics method. Based on the improved FRN model, the cross-section width distribution of the divergence duct is calculated from the given flow rate distribution. The shape of the divergence deflector is optimized by adjusting the flow rate distribution and using the improved model. The results indicate that the temperature difference of the battery cells decreases by more than 84% after the optimization, with the maximum temperature decreasing by more than 3.8 K. Furthermore, the optimized system performs better than those in the previous studies. Also, experiments are carried out to verify the effectiveness of the developed optimization method based on the improved FRN model.

Efficient optimization of parallel micro-channel heat sinks based on flow resistance network model

Electronics cooling is a critical issue affecting technological development. Parallel micro-channel heat sink (PMCHS) is widely applied for electronics cooling. However, the existing optimization methods are incapable to perform efficient design of three-dimensional liquid-cooled PMCHSs, impeding the thermal management of high power and volume-shrinking electronics. In this study, a flow resistance network (FRN) model is developed for structural optimization of three-dimensional liquid-cooled PMCHSs. Based on the uniform flow rate distribution, the FRN model is used to determine the optimized parallel channel widths and the optimized inlet deflector shape of the PMCHS. With the optimized parallel channel widths, the maximum temperature (Tmax) of the PMCHS is decreased by 4.0 K and the temperature standard deviation (σT) is decreased by 20%. With the optimized inlet deflector shape, Tmax and σT are reduced by 4.8 K and 14% respectively. The optimization method based on the developed FRN model for structural design of PMCHSs avoids multiple iterations of system parameters in existing optimization methods, showing its potential in high efficient thermal management of electronics.

Fast multilayer temperature distribution estimation for lithium-ion battery pack

Fast and accurate temperature estimation is crucial for ensuring battery packs' safety and operation performance. However, the full-scale online temperature estimation is still challenging. In this work, a novel reduced-order multi-physics model for a lithium-ion battery pack is proposed for real-time temperature distribution estimation, containing the distributed equivalent circuit model, the three-heat-source thermal model, and the flow resistance network model. The proposed model is conducted on a direct contact liquid-cooled battery pack composed of three modules connected in series. An online parameterization methodology with a closed loop observer is designed, and the key parameters can be automatically identified and corrected. The validation results suggest that the multilayer temperature distribution of cell, module, and pack levels can be commendably described under both steady and transient conditions, where the maximum error can be controlled within 2.8 °C. Besides, the temperature variation of the coolant can be estimated during the operation. The proposed model shows excellent potential in onboard temperature estimation with tens of milliseconds for each temperature update.

A novel combined model for energy consumption performance prediction in the secondary air system of gas turbine engines based on flow resistance network

Predicting the comprehensive energy consumption is challenging for the complicated secondary air system. To solve this problem, a universal flow resistance element has been constructed to describe different components more accurately. And a novel flow resistance network is proposed to calculate the system's energy consumption. This network can be analyzed by the flow resistance characteristics of its components to estimate the energy consumption of each component and the energy loss of the system. Furthermore, a flow resistance parameter is defined as a unique factor to determine the magnitude of flow resistance for each component. Compared to experimental and numerical results, both models demonstrate sufficient accuracy in calculating mass flow rates and entropy increments, with the maximum deviation less than 1.2%. The above two models are also applied to predict flow losses of elements with changes in pressure and inlet total temperature, with the maximum deviation less than 4.5%. Based on the flow resistance network, the aerodynamic performance of each element can be easily computed by the inlet and outlet boundary of this system, regardless of whether the elements are arranged in series or parallel.

Experimental and numerical investigation on efficient optimization of battery thermal management systems

Air-cooled battery thermal management systems are widely used in electric vehicles for cooling of battery pack. Design of air-cooled systems is in urgent need to enable the temperature and temperature difference in battery packs to locate within a reasonable range. In this work, a novel optimization method is proposed for efficient design of parallel air-cooled battery thermal management systems. The optimization method is developed by introducing simplified calculation models (heat transfer model and flow resistance network model) and setting identical average temperature of battery cells. This method obtains the optimized structural parameters by solving the simplified models, which is time-saving. Design of the parallel channel widths for different air-cooled systems is conducted to verify the effectiveness of the developed method. Results indicate that the temperature difference among batteries decreases by more than 72% with the maximum temperature decreased as well after the optimization. The optimized systems exhibit better heat dissipating performance than those using the previous optimization methods. Furthermore, experiments are carried out to examine the performance of the optimized system. The proposed optimization method shows great potential for efficient structural design of parallel air-cooled BTMSs.

A novel optimization method based on inverse calculation model for efficient design of battery thermal management system

Air-cooled parallel battery thermal management system (BTMS) is universally adopted in electric vehicles to ensure that temperature of battery packs locates within an optimum range. Thus, design of air-cooled BTMS to enhance its cooling performance is in need. In this study, an optimization method based on inverse flow resistance network model is proposed for efficient design of parallel BTMS. The inverse flow resistance network model is developed by taking structural parameters as the variables to be solved and supplementing constraint equation in the original flow resistance network model. Based on this inverse model, structural parameters of the system can be directly obtained once the flow rates among parallel channels are given. Furthermore, regulation of flow rates among parallel channels towards optimal distribution is carried out, which leads to optimal structural parameters of the system with the aids of the inverse calculation model. The proposed method is adopted to optimize the width distribution of parallel channels in BTMSs with different flow patterns. The results show that the temperature difference in battery pack after the optimization is reduced by at least 55%. Furthermore, the present optimized systems achieve better cooling performance than those in the previous study. Experiments are conducted to further demonstrate the effectiveness of the optimized systems for cooling performance improvement. The developed inverse model discloses the quantitative relationship between the flow rate distribution and structural parameters, and the proposed method based on this model optimizes the parallel BTMSs by searching the optimal flow rate distribution, which avoids the implement of repeated adjustments of structural parameters and the introduction of randomness operators in previous methods. The developed optimization is anticipated to guide the efficient design of parallel BTMS for enhancement of system performance.

Consistency analysis and resistance network design for vanadium redox flow battery stacks with a cell-resolved stack model

ABSTRACT The problem of non-uniform electrolyte distribution and the presence of shunt current greatly limit the system performance of vanadium redox flow batteries (VRFBs). It is thus critical to delicately design the electrolyte flow frame in VRFB stack such that the overall system efficiency and stack consistency can be improved. In this work, first, a cell-resolved VRFB stack model coupling the flow resistance network model and equivalent circuit model is developed and validated for a VRFB stack, which can be used for stack consistency and performance analysis. Then, sensitivity analysis is carried out to examine the impacts of the distribution channel and manifold resistances on electrolyte distribution uniformity and cell voltage consistency as well as system efficiency of the stack in detail. Based on the above sensitive analysis, the resistance network for a 20-cell VRFB stack is finally optimized by designing the non-uniform distribution channel resistances. It is proved that this proposed non-uniform resistance network design can further improve the electrolyte flow and the voltage distribution uniformity between cells as well as the system efficiency.

A direct optimization strategy based on field synergy equation for efficient design of battery thermal management system

Air-cooled battery thermal management system (BTMS) is critical for the safety and performance of electric vehicles. The system design needs to be optimized to achieve best thermal stability and uniformity. The current optimization methods for system design require empirical adjustment and contain randomness, which impedes to get the optimal system design. In this work, a direct optimization strategy based on field synergy equation is proposed for the optimal design of BTMS. Field synergy equation is introduced to calculate the optimal flow rate distribution in the system, which is combined with flow resistance network model to obtain the optimized structural parameters of the system. The developed strategy is adopted to optimize the parallel channel width distribution and plenum angle of BTMS. Computational fluid dynamics method and experiment are utilized to evaluate the cooling performance of BTMS. The results show that the temperature difference (ΔTmax) in battery pack after parallel channel width optimization is reduced by at least 49% without pressure drop increased, while ΔTmax after plenum angle optimization is reduced by at least 56% with pressure drop slightly increased. Mechanism of convective heat transfer optimization is taken into consideration by using field synergy equation in the proposed direct optimization strategy, which thus eliminates the burden of repeated adjustment of structural parameters and exhibits high efficiency for design of parallel cooling system. The developed optimization strategy is believed to guide the thermal design of battery packs to enhance their performance and safety.

A 3D macro-segment network model for vanadium redox flow battery with serpentine flow field

This paper presents a 3D macro-segment network model for a vanadium redox flow battery with serpentine flow field. The proposed network model is coupled of electrolyte flow module, species transfer module, charge transfer module. In flow resistance network module, the characteristics of electrolyte flow in the serpentine flow channel and under-rib convection in the porous electrode are all considered. In addition, the electrode intrusion and the electrode non-uniform structure caused by compression are taken into account. In species transfer network module, the convection, diffusion and migration between adjacent segments and reversible electrochemical reactions and self-discharge reactions inside the segment are all analyzed in the ion conservation equation. In charge transfer network module, each battery segment, which is composed of the channel, electrode and membrane segment in series, is connected in parallel and has the same output voltage. In this paper, the battery performance including charge-discharge voltages and cell pressure drop under different electrode compression ratios are validated. In the following, the battery performance under single and multiple charge-discharge cycle are investigated using the proposed network model. Besides, the field distribution of key parameters in terms of velocity, pressure, ions concentration and current density are analyzed and validated with finite element method model data. The proposed 3D macro-segment network model is not only able to effectively consider the distribution difference inside the battery caused by the flow field, but also capable of reducing the computational resources, which renders the network model is suitable for the fast prediction of battery performance.

A new structure optimization method for forced air-cooling system based on the simplified multi-physics model

Energy storage systems equipped with lithium-ion batteries are susceptible to fire and explosion hazards, especially when such batteries are used to power electric vehicles. One of the most important reasons for these undesirable consequences is the lack of an effective battery thermal management system. In this regard, an optimization method for the forced air-cooling system is introduced based on a simplified multi-physics simulation model. The simplified multi-physics model consists an electro-thermal coupling model and a flow resistance network model. The accuracy of the simplified multi-physics model is verified by comparison with experimental results. Subsequently, the deflector angle and cell space in the forced air-cooling system are optimized, respectively, based on the simplified multi-physics model, via an exhaustive search method and a genetic algorithm. Finally, the verification platform for the forced air-cooling system is built. After the optimization of deflector angle and cell space, the maximum temperature and temperature difference are limited to 38℃ and 2℃, with a reduction of about 30% and 80%, with respect to the unoptimized version. The consistency between the simulated and measured maximum temperature further confirms the effectiveness of the structure optimization method. In that, the method proposed in this paper is of great significance to shorten the time of structural optimization for forced air-cooling systems.

Multistage Digital-to-Analogue Chip Based on a Weighted Flow Resistance Network for Soft Actuators.

A control chip with a multistage flow-rate regulation function based on the correlation between the flow resistance and flow rate has been developed in this article. Compared with the traditional proportional solenoid valve, this kind of flow valve based on microfluidic technology has the characteristics of being light-weight and having no electric drive. It solves such technical problems as how the current digital microfluidic chip can only adjust the flow switch, and the adjustment of the flow rate is difficult. To linearize the output signal, we propose a design method of weighted resistance. The output flow is controlled by a 4-bit binary pressure signal. According to the binary value of the 4-bit pressure signal at the input, the output can achieve 16-stage flow adjustment. Furthermore, we integrate the three-dimensional flow resistance network, multilayer structure microvalve, and parallel fluid network into a single chip by using 3D printing to obtain a modular flow control unit. This structure enables the microflow control signal to be converted from a digital signal to an analogue signal (DA conversion), and is suitable for microflow driving components, such as in microfluidic chip sampling systems and proportional mixing systems. In the future, we expect this device to even be used in the automatic control system of a miniature pneumatic soft actuator.

Structure Optimization of Battery Thermal Management Systems Using Sensitivity Analysis and Stud Genetic Algorithms

Battery thermal management systems (BTMS) are hugely important in enhancing the lifecycle of batteries and promoting the development of electric vehicles. The cooling effect of BTMS can be improved by optimizing its structural parameters. In this paper, flow resistance and heat dissipation models were used to optimize the structure of BTMS, which were more efficient than the computational fluid dynamics method. Subsequently, five structural parameters that affect the temperature inside the battery pack were analyzed using single-factor sensitivity analysis under different inlet airflow rates, and three structural parameters were selected as the constraints of a stud genetic algorithm. In this stud genetic algorithm, the maximal temperature difference obtained by the heat dissipation model was within 5K as the constraint function, where the objective function minimized the overall area of the battery pack. The BTMS optimized by the stud genetic algorithm was reduced by 16% in the maximal temperature difference and saved 6% of the battery package area compared with the original BTMS. It can be concluded that the stud genetic algorithm combined with the flow resistance network and heat dissipation models can quickly and efficiently optimize the air-cooled BTMS to improve the cooling performance.

Experimental and numerical studies on an efficient transient heat transfer model for air-cooled battery thermal management systems

Air-cooled battery thermal management system (BTMS) is universally adopted in electric vehicles for temperature control of battery packs. In the present study, we develop an efficient transient model for accurately predicting the battery cell temperature in different types of parallel air-cooled BTMSs. A flow resistance network model for BTMS with I-type flow is established according to law of momentum conservation. Based on energy equations, a transient heat transfer model is derived to calculate the temperature distribution of battery pack in the BTMSs. The model results are in good agreement with experimental data, verifying the effectiveness and efficiency of this model. The deviations of Tmax and ΔTmax between the models and experiment are less than 1.5 K. Furthermore, by using the developed transient models, the deviations of Tmax and ΔTmax respectively decrease by 70% and 26%, in comparison with previous study. Finally, based on the developed models, the widths of parallel channels and divergence/convergence ducts in the BTMSs are designed, leading to remarkably enhanced cooling performance. The present study provides an efficient transient heat transfer model for parallel cooling systems, which can provide a deeper insight into the system performance and be applied to structural optimization of the systems.

Effects of Pressure Drop Characteristic due to Branching and Confluence on Development of Flow and Thermal Resistance Network Model of Finned Heat Sinks with Bypass

Effects of Pressure Drop Characteristic due to Branching and Confluence on Development of Flow and Thermal Resistance Network Model of Finned Heat Sinks with Bypass

Design of the structure of battery pack in parallel air-cooled battery thermal management system for cooling efficiency improvement

In this paper, the cell spacing distribution of the battery pack in the parallel air-cooled BTMS is designed to improve the cooling efficiency of the system. The flow resistance network model is used to calculate the airflow rates in the cooling channels. A modification factor is introduced to reduce the error of the model. The effectiveness of the model is verified by the computational fluid dynamics (CFD) calculation, and the CFD method is validated by the experimental air-cooled system with aluminum blocks. Combining with the improved flow resistance network model, an optimization strategy is adopted to optimize the battery cell spacings for the homogenization of the airflow rates among the cooling channels. Then an adjustment coefficient is introduced to adjust the airflow rates in the cooling channels for more uniform cell temperatures. The results of typical numerical cases indicate that the cooling efficiency of the BTMS is improved remarkably after the cell spacing optimization using the developed strategy. Compared to the original BTMS, the maximum temperature of the battery pack for the optimized BTMS is reduced by about 4.0 K, and the maximum cell temperature difference is reduced by more than 69% for various inlet airflow rates. Compared to the optimized BTMS in previous study, the maximum cell temperature difference for the present optimized BTMS is reduced by more than 25% for various inlet airflow rates.

Structure optimization of parallel air-cooled battery thermal management system with U-type flow for cooling efficiency improvement

In this paper, the cooling efficiency of the parallel air-cooled battery thermal management system (BTMS) with U-type flow is improved through optimizing the structure of the system. The flow resistance network model is developed to calculate the airflow rates of the cooling channels in the system. Based on the developed flow resistance network model, the angles of the plenums and the widths of the inlet and the outlet are optimized using the nested looped procedure and the numeration method. The numerical results of typical cases show that the temperature and the temperature difference among the battery cells cannot be effective reduced through arranging the angles of the plenums of the system, while optimizing the widths of the inlet and the outlet can remarkably improve the cooling efficiency of the BTMS. For the process with 5C discharge rate process, the temperature difference among the battery cells is reduced by 70% after optimization, with the power consumption reduced by 32%. Moreover, compared to the optimized BTMS in the previous study, the temperature difference among the battery cell for the present optimized BTMS is 43% lower, with power consumption reduced by 50%. The similar improvement can be achieved for various inlet airflow rates.

Configuration optimization of battery pack in parallel air-cooled battery thermal management system using an optimization strategy

Battery thermal management system (BTMS) is essential for heat dissipation of the battery pack to guarantee the safety of electric vehicles. Among the various BTMSs, the parallel air-cooled system is one of the most commonly used solutions. In this paper, the configuration of the battery pack in parallel air-cooled BTMS is optimized through arranging the spacings among the battery cells for cooling performance improvement. The flow resistance network model is introduced to calculate the velocities of the cooling channels. The heat transfer model is used to calculate the battery cell temperature. Combining these two models, an optimization strategy is proposed to optimize the configuration of the battery pack under the constant cell heat generation rate. The numerical results of typical cases show that the optimization strategy can obtain the final solution in only several times of adjustments of cell spacings. The cooling performance of the BTMS is improved remarkably after optimization. The maximum temperature difference is reduced by 42% and the maximum temperature of the battery pack is reduced slightly after optimization, with no increment on the total pressure drop of the system. Furthermore, the optimized BTMS still performs much better than the original one for various inlet flow rates and for the situation of unsteady heat generation rate.

Structure optimization of parallel air-cooled battery thermal management system

Battery thermal management system (BTMS) is critical to battery packs in electric vehicles, which significantly influences the service life of the battery packs and the performance of the electric vehicles. In this paper, the structure optimization of the parallel air-cooled BTMS is investigated to improve the cooling performance of the system. The flow resistance network model is introduced to calculate the velocities in the cooling channels of the system. The numerical results show that the velocities in the cooling channels calculated by the flow resistance network model are in good agreement with the ones calculated by CFD method, validating the effectiveness of the model. Furthermore, the model can save much calculation time, which is applicable to combine with the optimization approaches for structure optimization of BTMS. Subsequently, the structure of the BTMS is optimized through arranging the widths of the inlet divergence plenum and the outlet convergence plenum without changing the layout of the battery cells. Newton method is introduced to combine with the flow resistance network model to obtain the optimal plenum widths, with the target of minimizing the standard deviation of airflow velocities in the cooling channels. The optimization with fixed inlet flow rate and the one with fixed power consumption are both conducted. Three-dimensional CFD calculations for both the original BTMS and the optimized BTMS are performed, respectively. The results show that the cooling performance of the BTMS can be improved significantly after optimization using the proposed method. For the situation with fixed inlet flow rate and constant heat generation of the battery pack, the maximum temperature difference of the battery pack is reduced by 45% after optimization. For the situation with fixed power consumption and constant heat generation of the battery pack, the maximum temperature difference of the battery pack is reduced by 41% after optimization. Moreover, the maximum temperature of the battery pack is also reduced slightly after optimization. For the situation with fixed power consumption and unsteady heat generation of the battery pack, the maximum temperature differences of the battery pack are still reduced by 35% and 32% respectively for 4C and 5C discharge processes after optimization. It can be concluded that Newton method combined with the flow resistance network model is an effective method to optimize the structure of the parallel air-cooled BTMS and to improve the cooling performance of the system.