Multi-objective optimization design of B-pillar and rocker sub-systems of battery electric vehicle

Wu, Lijia; Chen, Tao; Li, Eric; Hu, Lin; Wang, Fang; Zou, Tiefang

doi:10.1007/s00158-021-03073-0

Cited by 29 publications

(9 citation statements)

References 56 publications

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“…Duan et al introduced an implicit parameterization method and a moving morphable component approach to improve joint structures, leading to a lighter vehicle body [11]. Li et al studied the dynamic bending performance of T joints using simulation analyses, optimizing the best structure of the B-pillar to minimize mass and enhance the mean crushing force [12]. Koricho et al conducted a series of finite element simulations to explore the correlations between mechanical properties and materials of vehicle joints, ultimately realizing joint structural optimization [13].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Vehicle Joints through Adaptive Stacking Model and Discrete Marine Predator Optimization Algorithm

Zhang

et al. 2023

Preprint

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The design of vehicle body joints is a critical aspect of the conceptual design process. Joint structures significantly affect the mechanical performance of vehicle bodies. However, due to the nonlinear relationship between joints and body performance, it is challenging to develop an explicit expression for optimization. Furthermore, traditional finite element analysis is impractical due to the vast number of possible joint configurations. Therefore, we propose a surrogate model-based optimization method to address this problem. First, we propose an intelligent adaptive stacking method (IASM) to establish the surrogate model. We evaluate the performance of IASM and other competitors on 34 benchmark functions and 3 open engineering projects, and IASM demonstrates the best predictive performance overall. Next, we construct joint modules with different configurations as candidate modules, which we connect to the vehicle body using beam units to build the simplified vehicle body (JMBB). JMBB significantly reduces the computational cost of finite element simulation, generating training samples for IASM. We then propose a discrete marine predator algorithm (DAMPA) to optimize the joints based on IASM. Compared to the genetic algorithm, DAMPA identifies joint modules with better mechanical performances. To validate the effectiveness of our method, we modify the base vehicle body using the optimized joints, resulting in a 7.4 kg reduction in body mass while enhancing four other mechanical metrics.

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Section: Introductionmentioning

confidence: 99%

Optimizing Vehicle Joints through Adaptive Stacking Model and Discrete Marine Predator Optimization Algorithm

Zhang

et al. 2023

Preprint

Self Cite

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“…Automobile lightweight technology can effectively achieve energy conservation and emission reduction and improve the endurance of electric vehicles 1,2 . As a critical force transmission and occupant protection component in a car's side collision, the B‐pillar can effectively absorb the energy generated by the side collision, thus limiting the energy intrusion into the passenger compartment 3 . Its lightweight level directly affects the side collision performance of its car.…”

Section: Introductionmentioning

confidence: 99%

“…1,2 As a critical force transmission and occupant protection component in a car's side collision, the B-pillar can effectively absorb the energy generated by the side collision, thus limiting the energy intrusion into the passenger compartment. 3 Its lightweight level directly affects the side collision performance of its car. On the premise of meeting various requirements, designing and optimizing a new structural hybrid material B-pillar can effectively improve the lightweight level and crash resistance of the B-pillar, which has important scientific significance and engineering prospects.…”

Section: Introductionmentioning

confidence: 99%

Research on the lightweight design and multilevel optimization method of B‐pillar of hybrid material based on side‐impact safety and multicriteria decision‐making

Zhang,

Lu,

Huang

et al. 2023

Polymer Composites

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This paper designs and optimizes a new structure hybrid material B‐pillar assembly. Establish a finite element analysis model for the side impact test of an electric vehicle to verify the model's accuracy. Construct a finite element model of the hybrid material B‐pillar assembly. Combined with the static performance analysis of the B‐pillar, the laminate design of the carbon fiber composite B‐pillar reinforcement plate and optimization. For the outer and inner panels of the B‐pillar, the surrogate model method and the multiobjective optimization method are combined to set 11 design variables and 13 responses. The optimal Latin hypercube design method was used to randomly sample each design variable and fit the radial basis function (RBF) approximate model. The modified second‐generation non‐dominated sorting genetic algorithm (MNSGA‐II) was used to carry out multiobjective optimization of the mixed material B‐pillar assembly, and the multicriteria decision‐making method was used to obtain the optimal solution for the Pareto solution set. A drop weight impact test was performed on the hybrid material B‐pillar assembly. The results showed that the peak collision force of the hybrid material B‐pillar was reduced by 43.7% compared with the original steel B‐pillar, the specific energy absorption was increased by 17.5%, and the side impact safety performance was better. After optimization, the weight of the mixed material B‐column was reduced by 26.44%. The improvement rates of the intrusion amount at P2 and the intrusion speed at P1 were 23.99% and 0.63%, respectively, and the lightweight effect and side impact safety were significantly improved.Highlights The finite element analysis parameters of carbon fiber composite materials were constructed through experiments, and the basis for simulation analysis under various working conditions of the B‐pillar based on performance‐driven optimization was established. A hybrid material B‐pillar design method is proposed, which consists of a variable‐thickness high‐strength steel B‐pillar outer plate, a variable‐thickness high‐strength steel B‐pillar inner plate, and a carbon fiber composite B‐pillar reinforcement plate. The super layer of the carbon fiber composite B‐pillar reinforcement plate was optimized and the laying plan of the carbon fiber composite B‐pillar reinforcement plate was determined. Performance‐driven optimization is adopted to realize the collaboration of multilevel design and optimization methods such as B‐pillar conceptual design, detailed design, and multiobjective optimization. A modified NSGA‐II algorithm was proposed and combined with the multicriteria decision‐making method and the entropy‐weighted gray relation analysis method to determine the Pareto optimal solution and the optimal design scheme for the mixed material B‐pillar.

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“…[11][12][13][14][15][16] However, battery safety is another problem to be taken care of from the point of human safety due to locating the flammable and explosive material batteries just under the seats at EVs and HEVs or just carrying these power systems on expensive UAVs or helicopters when we consider crash, puncturing, flaming, threshold alerts on the circuits. Occasions and malfunction of batteries related to accidents or operation [17][18][19][20][21][22][23][24] urge the researchers to find optimized solutions considering safety regulation tests such as shock, drop, penetration, rollover, immersion, crush, thermal stability, and thermal insulation that show the deformation on the cells. The battery cell structure is generally the same for all that are classified according to active material.…”

Section: Introductionmentioning

confidence: 99%

Dynamic compression and impact analyses of the lattice structures for battery safety

Gültekin

YAHŞİ

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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In this study, a battery pack consisting of 18650-lithium-ion cells and battery housing was designed considering lattice structures instead of the plain sheet to improve crashworthiness. The behavior of lattice structures, including a novel design, cross semicircle, semicircle lattices, and topology-optimized model, in total seven different lattice models in dynamic compression and impact loading were examined. Displacement, energy absorption, and specific energy absorption values were compared with the 1.5 mm thick plain sheet model, which is common in the market. In the dynamic compression loading, honeycomb, and plain sheet models absorb more energy with the value of 97.34, and 88.67 J, respectively. Specific energy absorption is best for the plain sheet with the value of 3122.05 J/g, but honeycomb and cross semicircle lattices still have an impressive result of 2923.04, and 2158.30 J/g respectively. On the other hand, in the impact loading, the plain sheet is causing the jellyroll deformation with the highest value of 141.65 MPa, while the best protective structure is 3D kagome with a value of 4.85 MPa. However, the cross-semicircle keeps an average safety performance for both loading conditions.

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Multi-objective optimization design of B-pillar and rocker sub-systems of battery electric vehicle

Cited by 29 publications

References 56 publications

Optimizing Vehicle Joints through Adaptive Stacking Model and Discrete Marine Predator Optimization Algorithm

Optimizing Vehicle Joints through Adaptive Stacking Model and Discrete Marine Predator Optimization Algorithm

Research on the lightweight design and multilevel optimization method of B‐pillar of hybrid material based on side‐impact safety and multicriteria decision‐making

Dynamic compression and impact analyses of the lattice structures for battery safety

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