World Electric Vehicle Journal

Reference measurements can affect battery state-of-health (SOH) estimates across operating conditions. We compare reference protocols using fixed local discharge features, regression settings, training records, and evaluation rules. XJTU Batch-3 provides 4487 training records and Batch-4 provides 4639 test records from eight batteries per batch at five discharge rates. Across 40 battery–rate groups, the reference-free macro-group mean absolute error (MAE) was 0.015887. Original single-1C (B3:r3/B4:r7), early single-1C (B3:r3/B4:r3), and same-rate normalization yielded MAEs of 0.014058, 0.014584, and 0.014643, respectively. Battery-cluster bootstrap intervals for improvement over reference-free had positive lower bounds for original single-1C and fixed 0.5C; intervals for early single-1C and same-rate included zero. The lowest average error did not coincide with the lowest worst-group error. At 3C, same-rate normalization improved on the original single-1C for all eight batteries, with a mean MAE reduction of 0.006663. Separate NASA leave-one-cell-out and XJTU Batch-5 holdout analyses examined local-feature applicability under random load. Reference protocols should specify both operating condition and measurement selection, with conclusions limited by the eight target batteries.

Electric cars and electric two-wheelers are transforming urban mobility along two parallel tracks, yet the two are usually studied separately, and evidence from a single policy environment in which both diffuse simultaneously remains scarce. Using monthly full-population vehicle registration records for 2000–2026 and official public charging and parking statistics from Macao, we compare the diffusion dynamics of the two tracks within one dense city. Threshold-crossing analysis shows that around the 2022 replacement subsidy and the accompanying build-out of public charging spots, the electric share of new two-wheeler registrations rose from 5% to 25% within 18 months, less than half the 37 months taken by cars; from 2024 to 2026, the two-wheeler share reached parity with and in most months exceeded that of cars. Lead-lag tests indicate that charging-spot expansion precedes two-wheeler fleet growth (Granger lag-1 p = 0.030; unfiltered distributed-lag joint p < 0.001), a pattern that weakens under seasonal adjustment and detrending (p = 0.186); no such precedence appears on the car track. Ample car parking plausibly favors private charging—a hypothesis, not a measured mechanism: parking spots do not establish charger access. Where two-wheelers are numerous and private parking scarce, public charging may enable their electrification, pending charging-access data.

Effective diagnosis of electric bearing faults, especially weak early-stage faults, remains challenging due to complex rotational-speed conditions and external noise. Although the velocity-guided chirplet transform (VGCT) can effectively characterize nonstationary components, it requires synchronized rotational-speed information, which is often difficult to obtain in practice. To this end, this paper proposes a prior-knowledge-enhanced velocity-guided chirplet transform (PKVGCT) for fault diagnosis without prior rotational-speed information. PKVGCT includes two stages. In the first stage, multiple candidate instantaneous frequencies (IFs) are obtained via peak searching and are smoothed by a second-order difference operator to support obtaining a reliable guideline. In the second stage, the manually selected guideline is further used in the analysis of VGCT, and simultaneously a weak-noise energy filtering mechanism is applied to ultimately yield a high-quality time-frequency (TF) representation (TFR). In numerical analysis, the qualitative analysis of the TFR results, the mean relative error (MRE)-based quantitative analysis, and the robustness analysis under different noise levels all demonstrate the superior performance of PKVGCT. With two experimental cases, the effectiveness of PKVGCT in practical applications is fully demonstrated.