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Multi-objective optimization of PCM-fin structure for staggered Li-ion battery packs

Qiu Chenghui, Wu Chongtian, Yuan Xiaolu, Wu Linxu, Yang Jiaming, Shi Hong

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

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Vol. 71, nr 4

art. no. e145677

EN

Endurance capability is a key indicator to evaluate the performance of electric vehicles. Improving the energy density of battery packs in a limited space while ensuring the safety of the vehicle is one of the currently used technological solutions. Accordingly, a small space and high energy density battery arrangement scheme is proposed in this paper. The comprehensive performance of two battery packs based on the same volume and different space arrangements is compared. Further, based on the same thermal management system (PCM-fin system), the thermal performance of staggered battery packs with high energy density is numerically simulated with different fin structures, and the optimal fin structure parameters for staggered battery packs at a 3C discharge rate are determined using the entropy weight-TOPSIS method. The result reveals that increasing the contact thickness between the fin and the battery (X) can reduce the maximum temperature, but weaken temperature homogeneity. Moreover, the change of fin width (A) has no significant effect on the heat dissipation performance of the battery pack. Entropy weight-TOPSIS method objectively assigns weights to both maximum temperature (Tmax) and temperature difference (DT) and determines the optimal solution for the cooling system fin parameters. It is found that when X = 0:67 mm, A = 0:6 mm, the staggered battery pack holds the best comprehensive performance.

2

A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor

Knypiński Łukasz

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

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Vol. 71, nr 1

art. no. e144586

EN

The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.

3

Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm

Yilmaz Mehmet, Dede Tayfun, Grzywiński Maksym

Budownictwo o Zoptymalizowanym Potencjale Energetycznym

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2023

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Vol. 12

79--86

EN

Safety plays a crucial role in construction projects. Safety risks encompass potential hazards such as work accidents, injuries, and security. Consequently, it is important to effectively manage these risks with equal emphasis on time and cost considerations during the project planning phase. Within the scope of this research, the grid and archive-based Grey Wolf Optimizer (GWO) algorithm was employed to investigate multi-objective time-cost-risk problems. By employing the GWO, multiple Pareto solutions were provided to the decisionmaker, facilitating improved decision-making. It was determined that the GWO algorithm yields better results in time-cost-risk problems compared to the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms.

4

Static and dynamic impact performance optimization of CFRP/Al bolt joint coupling structure-lay-up-connection parameters

Xu Wenchao, Wang Dengfeng

Archives of Civil and Mechanical Engineering

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2022

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Vol. 22, no. 3

art. no. e118

EN

Static shearing, drawing, and dynamic impact test schemes of carbon fber reinforced polymer (CFRP)/aluminum alloy (Al) bolt joint were designed. The fnite element model of the CFRP/Al bolt joint was established, and the failure modes of the joints under the static and dynamic impact conditions were analyzed. The structure, lay-up, and connection parameters of the joint were defned as design variables, and the static and dynamic impact performance indicators of the joint and the lay-up numbers of the CFRP sheet were defned as optimization objectives. Integrated multiobjective optimization was conducted for joints, employing the radial basis function neural network (RBFNN) surrogate model, elitist nondominated sorting genetic (NSGA-II) algorithm, and entropy-technique for order preference by similarity to ideal solution (E-TOPSIS) decision method. The best trade-of solution was obtained, and the optimal design variables were determined. The optimized joint was fabricated, and static and dynamic impact tests were carried out. The test and simulation results were compared to verify the efectiveness of simulation and optimization.

5

Experimental and numerical investigation on the multi-optimization of reinforcing the side members of the vehicle structure

Zahedan Nima, Ahmadi Hamed, Liaghat Gholam Hossein

Archives of Civil and Mechanical Engineering

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2022

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Vol. 22, no. 1

art. no. e25, 2022

EN

The aim of this study is to investigate the improvement in the strength of a top-hat profile hollow-section beam used in a vehicle structure by attaching different shapes of internal reinforcements. The base structure of the beam was first considered as a hat-shape structure which was jointed to a flat plate using spot-welds. Three types of sheet metal reinforcements were formed and attached inside the beam’s structure. Then, they were tested experimentally under low-velocity lateral impact. Also, a numerical simulation is being developed using LS-DYNA explicit code and validated using experimental data. Valid numerical configuration is used to conduct an optimization study on cross-sectional shape of the internal reinforcing component. Optimizations are carried out using single- and multi-objective methods based on Genetic Algorithm approach and the suggested optimum solutions are compared with experimental results. Moreover, to discuss the feasibility of applied reinforcements on side section of a vehicle’s body-in-white, a realistic side-pole crash test is simulated using a validated vehicle model and performance of improved chassis is compared with basic model and results are presented, discussed and commented upon.

6

Verified methods for computing Pareto sets: General algorithmic analysis

G.-Tóth B., Kreinovich V.

International Journal of Applied Mathematics and Computer Science

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2009

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Vol. 19, no 3

369-380

EN

In many engineering problems, we face multi-objective optimization, with several objective functions f1, . . . , fn. We want to provide the user with the Pareto set-a set of all possible solutions x which cannot be improved in all categories (i.e., for which fj (x') fj (x) for all j and fj(x') > fj(x) for some j is impossible). The user should be able to select an appropriate trade-off between, say, cost and durability. We extend the general results about (verified) algorithmic computability of maxima locations to show that Pareto sets can also be computed.