Lightweight design of differential case based on particle swarm optimization algorithm

The lightweight design for automotive parts and components is a complex, multi-constrained problem concerning system optimization and satisfies various structural performance requirements. Existing studies on the lightweight design for automotive parts and components primarily focus on the automobile body design. Most of them focus on plastic material rather than the castings widely used in automobiles. This paper proposes a lightweight design for the casting of the differential mechanism shell in the assembly of the automotive drive axle. The paper focuses on the shell of the automotive differential mechanism and proposes a design method for optimization based on the combination of Particle swarm optimization algorithm and parameterized model. The main contents include: to first establish a parameterized, three-dimensional model for the differential mechanism shell, calculate the modal numerical values of the first 6 orders of the differential mechanism shell, derive the maximum modal numerical value among the first 6 orders, i.e. 6.22% only through modal test contrast, thus verify the correctness of the model. Second, it establishes three limiting conditions of the differential mechanism, including: the automotive advancing condition during transmission with highest torque of the engine and fist gear of the gear box, and automotive reversing condition and twisting fatigue condition with the highest torque of the engine and reverse gear of the gear box. Based on the PSO algorithm, the paper establishes an optimization design with the goal of minimum mass and maximum root-mean-square value of the safety coefficients and a lightweight design in combination with the parameterized model of the differential mechanism shell. It can be inferred by comparing the relevant performance parameters of the differential mechanism shell before and after the lightweight design that: the maximum stress of optimized model decreases by 12.55% under the advancing condition; the maximum stress of optimized model is 5.74% under the reversing condition; under the condition of torsion fatigue, the minimum safety coefficient has risen to 1.35 from 1.12 after optimization; the shell weight has fallen to 5.67 kg from 6.26 kg after optimization with reduction of 10.4%; and the above analyses demonstrate that the lightweight design is successful.