Browsing by Author "BULUT, EMRE"

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A comparative study on conventional and hybrid quenching hot forming methods of 22mnb5 steel for mechanical properties and microstructure
(Springer, 2022-08-01) Eşiyok, Ferdi; Ertan, Rukiye; Sevilgen, Gökhan; Bulut, Emre; Özturk, Ferruh; Alyay, İlhan; Abi, Tuğçe Turan; ERTAN, RUKİYE; SEVİLGEN, GÖKHAN; BULUT, EMRE; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; 0000-0002-7746-2014; 0000-0001-9159-5000; KIH-2391-2024; JIW-7185-2023; JCO-2416-2023; ABG-3444-2020
In this paper, the conventional hot forming and hybrid quenching hot forming processes of Al-Si-coated 22MnB5 steel sheet were investigated and compared at 0.5 s-15 s holding times in the press tool related to the mechanical properties, microstructure, and dimensional accuracy. The conventional hot forming method is classified as a direct method and an indirect method. Both methods have limitations due to processing time and cooling of the press tool. To speed up the process, an alternative cooling method based on spray or jet cooling was used outside of the die tool. The hybrid quenching method involves hot forming and spray cooling process. This method, using spray parameters, provides more effective control in mechanical properties and microstructure compared to the conventional method by using spray parameters. Vickers hardness tests and tensile tests were carried out to compare mechanical properties. Changes in the microstructure of the materials were investigated using an optical microscope. The results show that spray cooling can be used as part of quenching in the hot forming process by reducing the holding time in the press tool by 97%. However, the microstructure, mechanical properties, and geometry deviations of the stamped parts are still below tolerances after the hybrid quenching hot forming process. The use of the hybrid quenching method with multi-point nozzles in the hot forming process resulted in sheet hardness up to 470 HV1 and 8% elongation with tensile strength of 1500 MPa.
A new approach for battery thermal management system design based on grey relational analysis and latin hypercube sampling
(Elsevier, 2021-09-16) Bulut, Emre; Albak, Emre İsa; Sevilgen, Gökhan; Öztürk, Ferruh; BULUT, EMRE; ALBAK, EMRE İSA; SEVİLGEN, GÖKHAN; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü; Bursa Uludağ Üniversitesi/Gemlik Asım Kocabıyık Meslek Yüksekokulu/Hibrit ve Elektrikli Araç Teknolojisi; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; ABG-3444-2020; AAG-8907-2021; I-9483-2017; JCO-2416-2023; FRD-1816-2022
A liquid cooling system is an effective type of battery cooling system on which many studies are presented nowadays. In this research, the effects of the mass flow rate and number of channels on the maximum temperature and pressure drop are investigated for multi-channel serpentine cooling plates. A new approach with LHS and GRA is used to obtain the optimum ranges of design parameters to minimize the pressure drop, maximum temperature and to maximize the convective heat transfer coefficient. In this study, the values of the parameters for the numerical modeling are obtained by the experiments. The width and height of the serpentine channel and mass flow rate are chosen as input parameters and the pressure drop, convective heat transfer coefficient and maximum temperature are selected as output parameters. Comparing with the base design, the optimized design provided up to 40.3% decrease in the pressure drop with a penalty of 11.3% decrease in the convective heat transfer coefficient with a slight decrease in the maximum temperature. The proposed approach can be used to design better cooling plates to keep the batteries in safe temperature ranges and to reduce the power consumption by optimizing the pressure drop and maximum temperature values.
A new approach for battery thermal management system design based on grey relational analysis and latin hypercube sampling
(Elsevier, 2021-09-16) Bulut, Emre; BULUT, EMRE; Sevilgen, Gökhan; SEVİLGEN, GÖKHAN; Öztürk, Ferruh; ÖZTÜRK, FERRUH; Albak, Emre İsa; ALBAK, EMRE İSA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Gemlik Asım Kocabıyık Meslek Yüksekokulu.; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; ABG-3444-2020; AAG-8907-2021; I-9483-2017
A liquid cooling system is an effective type of battery cooling system on which many studies are presented nowadays. In this research, the effects of the mass flow rate and number of channels on the maximum temperature and pressure drop are investigated for multi-channel serpentine cooling plates. A new approach with LHS and GRA is used to obtain the optimum ranges of design parameters to minimize the pressure drop, maximum temperature and to maximize the convective heat transfer coefficient. In this study, the values of the parameters for the numerical modeling are obtained by the experiments. The width and height of the serpentine channel and mass flow rate are chosen as input parameters and the pressure drop, convective heat transfer coefficient and maximum temperature are selected as output parameters. Comparing with the base design, the optimized design provided up to 40.3% decrease in the pressure drop with a penalty of 11.3% decrease in the convective heat transfer coefficient with a slight decrease in the maximum temperature. The proposed approach can be used to design better cooling plates to keep the batteries in safe temperature ranges and to reduce the power consumption by optimizing the pressure drop and maximum temperature values.
Estimation of energy management strategy using neural-network-based surrogate model for range extended vehicle
(Mdpi, 2022-12-14) Türker, Erkan; Bulut, Emre; Kahraman, Arda; Çakıcı, Mehmet; Öztürk, Ferruh; Türker, Erkan; BULUT, EMRE; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; 0000-0001-9159-5000; 0000-0003-0150-8052; JCO-2416-2023; AAG-8907-2021; CDI-5654-2022; JIW-7185-2023
In this paper, an energy-management strategy based on fuel economy is presented to achieve a further range increase for range-extended light commercial vehicles. Estimation of the energy-management strategy was carried out using a neural-network-based surrogate model for an range-extended vehicle. Surrogate-based optimization plays an important role in optimization problems, which are based on complex structures with uncertainties in data sets due to various conditions. Neural networks have advantages in creating surrogate-based models in cases of complex problems with uncertainties in data sets to evaluate the process and estimate the outputs. This study discusses additional power-unit applications and vehicle integration for a light commercial electric vehicle. It provides preliminary design work and techniques for identifying NVH problems in particular. SIMULINK and neural-network-based surrogate models are established, and the changeable parameters of the vehicle, such as mass, battery/fuel-tank capacity, internal combustion engine power and electric motor power units are simulated in different dynamic and static conditions to determine an energy-management strategy for a range-extended vehicle based on fuel economy under various conditions. It was seen that APU parameters and an energy-management strategy significantly affected the fuel consumption of REX. A neural-network-based surrogate-model approach gave high-precision results in predicting the operating strategy according to different loading conditions to reduce fuel consumption. In some cases, it can be required to determine the fuel consumption results in various conditions with the variables, which may be out-of-boundary conditions. It was seen that the proposed neural-network-model also offers higher prediction ability in cases of unexpected results in data sets of various conditions compared to regression analysis. The results show that estimation and optimization of energy management using a neural-network-based surrogate model can be achieved by adapting the operating strategy according to different loading conditions to reduce fuel consumption. This study presents an approach for future new vehicle projects by transforming a prototype light commercial electric vehicle to REX. The proposed approach was developed to design the most efficient range-extended vehicle by changing all variables without costly computations and time-consuming analysis. It is possible to generate variable data sets and to have reference knowledge for future vehicle projects.
Multi-objective optimization of liquid cooling system for a twelve-cell battery module
(Begell House Inc, 2022-01-01) Bulut, Emre; Albak, Emre İsa; Sevilgen, Gökhan; Öztürk, Ferruh; BULUT, EMRE; ALBAK, EMRE İSA; SEVİLGEN, GÖKHAN; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Gemlik Asım Kocabıyık Meslek Yüksekokulu/Hibrit ve Elektrikli Araç Teknolojisi Bölümü.; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; I-9483-2017; AAG-8907-2021; JCO-2416-2023; FRD-1816-2022
In this research, two cooling plates with six parallel channels are designed for a twelve-cell battery module. The heat generated by a Li-ion battery cell is numerically modeled, and the numerical model is validated with the experimental data. The temperature difference of the battery cells in the battery module is an important factor for the capacity usage and cycle life of a battery module. The aim of this study is to design an optimum cooling system that will increase the cycle life of the batteries by decreasing the temperature difference and reducing the parasitic power consumption of the pump by reducing the pressure drop. The channel height, channel width, and the ratio of the outlet height to the inlet height are selected as design variables. In recent years, several evolutionary multi-objective optimization techniques have been presented to improve the performance of thermal management systems. In this study, CMOPSO is used for the optimization of the liquid cooling system. The results of the NSGA-II, NSGA-III, MOPSO, and CMOPSO techniques are evaluated to compare the efficiency of different optimization techniques. The results of four different multi-objective optimization methods are close to each other and have good agreement with the CFD results to reduce the temperature difference and pressure drop. A 30.3% decrease in the temperature difference and a 5.3% decrease in the total pressure drop are achieved with CMOPSO as the optimization technique. The results show the effectiveness of CMOPSO as the optimization technique for the design of battery cooling systems.
Prediction and optimization of the design decisions of liquid cooling systems of battery modules using artificial neural networks
(Wiley-Hindawi, 2022-01-03) Bulut, Emre; Albak, Emre İsa; Sevilgen, Gökhan; Öztürk, Ferruh; BULUT, EMRE; ALBAK, EMRE İSA; SEVİLGEN, GÖKHAN; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Gemlik Asım Kocabıyık Meslek Yüksekokulu/Hibrit ve Elektrikli Araç Teknolojisi.; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; I-9483-2017; ABG-3444-2020; AAG-8907-2021; FRD-1816-2022
Liquid cooling systems are effective for keeping the battery modules in the safe temperature range. This study focuses on decreasing the power consumption of the pump without compromising the cooling performance. Artificial neural network (ANN) models are created to predict the effects of the height and width of the cooling channel and the mass flow rate on the maximum temperature, convective heat transfer coefficient, and pressure drop. The ANN models are used as surrogate models for the design and optimization of the liquid cooling battery system. Particle swarm optimization (PSO) and genetic algorithm (GA), which are commonly utilized optimization methods in many areas, and chaos game optimization (CGO) and coot optimization algorithm (COOT) methods, which are recently presented methods, are adopted to minimize the power consumption of the pump. The results are compared in terms of computational performance and best, worst, average, and SD values. Despite all of the optimization methods used giving similar results, the CGO method comes forward due to fast converging, SD, and finding the minimum power consumption of the pump among other optimization methods. A 22.4% decrease in the power consumption of the pump is achieved with the use of the ANN-based CGO method while conserving the cooling performance. When comparing the ANN predicted and CFD results, the relative errors are less than 1%.
Smart cooling design using dual loop cooling to increase engine efficiency and decrease fuel emissions with artificial intelligence
(Elsevier, 2022-10-26) Kula, Sinan; Bulut, Emre; Altay, Esad; Sümer, Osman; Öztürk, Ferruh; Kula, Sinan; BULUT, EMRE; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; 0000-0001-9159-5000; JCO-2416-2023; HGN-4395-2022; JGV-6240-2023
In this study, smart cooling design and optimization, which is based on dual loop cooling system, is used to increase the efficiency of the engine and decrease the fuel emission levels with the artificial intelligence approach. Dual circuit cooling system is used to cool down the charged air and condenser for the 1.6 lt turbocharged diesel engine. The main objective is to increase the efficiency of the engine and decrease the fuel emission levels with smart cooling system design using 1D analysis, experimental tests and neural networks. Water-cooled air charger and condenser are placed separately on engine bay. Whereas, similar applications have been used for these modules integrated on the engine itself. Artificial Neural Network approach is applied in order to optimize the water cooled air charger sizing. Input data is generated by using 1D model within the correlation of experimental test results both on dyno and road conditions. Experimental and 1D analysis data comparison shows that they are very coherent. Results showed that efficiency of the engine is increased and CO2 (g/km) emission levels are decreased about 4,1% in WLTP cycle. It's obtained with efficient dual loop cooling system and optimization based on 1D model and ANN approach.
The investigation of the effects of spray parameters on the thermal and mechanical properties of 22MnB5 steel during hybrid quenching process
(Begell House, 2021-01-01) Sevilgen, Gökhan; Ertan, Rukiye; Bulut, Emre; Öztürk, Ferruh; Eşiyok, Ferdi; Abi, Tuğçe Turan; Alyay, İlhan; SEVİLGEN, GÖKHAN; ERTAN, RUKİYE; BULUT, EMRE; ÖZTÜRK, FERRUH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; 0000-0002-7746-2014; 0000-0001-9159-5000; ABG-3444-2020; KIH-2391-2024; AAG-8907-2021; JIW-7185-2023
In this paper, the investigation of the effects of spray parameters on the thermal and mechanical properties of 22MnB5 steel during the hybrid quenching (HQ) process was performed. The HQ method presented in this study includes early removal of hot-stamped parts from the die and transfer to an external multinozzle spray cooling device. The proposed method was developed due to the need for improving disadvantages of the traditional hot stamping process such as complexity of controlling the cooling rate during die quenching by using cooling channels and of providing the reduced tool contact surface temperature after a certain cycle of the hot stamping process. This paper focuses on the temperature distribution and mechanical characteristics of high-strength 22MnB5 steel during the HQ process. Moreover, the methodology developed in this paper can be used to get tailored parts where the cooling rates are locally chosen to achieve structures with graded properties, i.e., to allow local modification of final mechanical properties in order to provide high energy absorption to enhance the crashworthiness of the whole component and thus to improve the vehicle safety performance. The three-dimensional numerical model of spray cooling was also developed by using the computational fluid dynamics (CFD) method to get the suitable process parameters such as spray height and initial blank temperature and to present the detailed heat transfer analysis of hot-stamped parts during the hybrid quenching process.