Uncertainty-Aware Lightweight Design of CFRP Battery Enclosure Under Extreme Cold Side-Pole Impact via Bayesian Surrogates

Mass M (kg) and peak intrusion L (mm) are jointly minimized for a CFRP-enabled battery pack enclosure under the GB 38031-2025 −40° side-pole extrusion condition. A 50-run explicit FE design of experiments is conducted and deterministically partitioned into 37/5/5/3 for initial training, two sequential enrichment batches, and an independent hold-out test. Bayesian additive regression trees are trained as the primary surrogates for M, L, and Stress, and stress acceptability is enforced through a probability-of-feasibility (PoF) gate anchored to a baseline-scaled cap, σlim = 1.2 σbase = 410.4 MPa. NSGA-II performed on the feasible surrogate landscape yields a bimodal feasible non-dominated set. The two branches correspond to two discrete levels of a key thickness variable x4: a low-mass regime (n = 106) with M = 100.61–104.81 kg and L = 5.430–5.516 mm at x4 ≈ 5.60 mm, and a stiffer regime (n = 94) with M = 110.69–115.08 kg and L = 5.362–5.430 mm at x4 ≈ 8.00 mm. PoF screening eliminates part of the intermediate region where feasibility confidence is insufficient. Independent FE reruns further indicate that the PoF gate reduces deterministic misclassification near the stress boundary (e.g., one near-threshold candidate exceeds σlim, whereas others satisfy the cap with margin). Overall, the proposed workflow offers a traceable lightweighting route under extreme-cold uncertainty within a constrained FE budget.