Robust multi-objective optimization of helical gears for electric vehicle transmissions

Volume-Efficiency Trade-Off Optimization of Two-Stage Helical Gearboxes via MOEA/D-DE Algorithm

The design of two-stage helical gearboxes inherently involves a trade-off between structural compactness and transmission efficiency. In this study, a multi-objective optimization framework based on the MOEA/D-DE (Multi-Objective Evolutionary Algorithm based on Decomposition with Differential Evolution) is proposed to...

Kinematic Symmetry-Driven Multi-Objective Collaborative Design of a Rigid Crank–Rocker Mechanism

To address the persistent challenges in optimizing the transmission performance of crank-rocker mechanisms—namely, the inaccuracies of local static evaluation models, the non-linear coupling constraints among multiple objectives, and the difficulties of navigating discontinuous and restricted solution spaces—this paper...

Multi-Objective Optimization and Global Design for Active Magnetic Dry Friction Damper Actuators

To address the tradeoff among high force, fast response, and compact volume in active magnetic dry friction dampers, this paper proposes a systematic multi-objective optimization framework centered on an interpretable global design surface. A parametric analytical model mapping the electromechanical couplings is establ...

Application of multi-objective genetic algorithm in the structural optimization of battery box for new energy vehicles

As the rapid development of new energy vehicles places increasingly stringent requirements on battery safety, lightweight design, and thermal management, the structural optimization of battery boxes has become a critical engineering challenge. To address the conflicting objectives among structural strength, heat dissip...

An integrated optimization method for multi-class parameters and multi-dimensional objectives: Application to an advanced transmission

Current transmission design methodologies often optimize single parameters or physical fields, while conventional heuristic algorithms suffer from premature convergence and lack interpretability. To address these limitations, this paper proposes an integrated optimization design method for planetary gear sets and wet c...

Experimental identification and robust optimization of spindle–bearing systems with reliability constraints