Exhaust gas recirculation (EGR) and selective catalytic reduction (SCR) have become important technologies to reduce the NO _x emission of heavy-duty diesel engines and meet the increasingly stringent emission regulations. This paper studied the effect of EGR combined with SCR on the NO _x emission characteristics of a heavy-duty diesel engine based on the engine bench test. The results showed that the NO reduction rate of EGR-coupled SCR increased with the increase of engine load, and the effect was no longer significant when the NO reduction rate exceeded a certain limit under the same working conditions. EGR combined with SCR has little effect on NO₂ emission reduction, and the increase of engine speed can significantly improve the efficiency of the NO₂ reduction rate at 75 and 100% load. 25% opening of the EGR valve (OEV) and 50% OEV have very similar effects on the NO _x reduction rate when the engine speed is at a low level. Compared with low engine speeds, increased OEV or ammonia NO _x molar ratio (ANR) had a more obvious effect on the NO _x reduction rate at high engine speeds. SCR combined with low valve-opening EGR had a more significant effect on the NO _x reduction rate. The increase of OEV led to the increase of fuel consumption rate, but the effect on the fuel consumption rate decreased gradually with the increase of diesel engine speed. Meanwhile, this study optimized the matching relationship between OEV and ANR based on the data of the genetic algorithm, which provides a theoretical research method and application basis for diesel engine-matching of EGR and SCR.

With the continuous upgrading of emission regulations, NOx emission limit is becoming more and more strict, especially in the cold start phase. Passive NOx absorber (PNA) can adsorb NOx at a relatively low exhaust temperature, electrically heated catalyst (EHC) has great potential to improve exhaust gas temperature and reduce pollutant emissions of diesel engines at cold start conditions, while experimental research on the combined use of these two kinds of catalysts and the coupling mode of the electrically heated catalyst and the aftertreatment system under the cold start condition are lacking. In this paper, under a certain cold start and medium-high temperature phase, the exhaust gas temperature and emission characteristics of PNA, EHC and aftertreatment system under different coupling modes were studied. Results showed that the average inlet temperature of diesel oxidation catalyst (DOC) and selective catalytic reduction catalyst (SCR) integrated into diesel particulate filter (SDPF) increased by 246.35 ℃ and 126.09 ℃ respectively under the coupling mode of PNA+EHC+DOC+ SDPF+SCR during cold start phase. The inlet temperature of DOC was not affected, and the average inlet temperature of SDPF increased by 200.52 ℃ under the coupling mode of PNA+DOC+EHC+SDPF+SCR. In terms of emissions, the effective NOx adsorption range of PNA reached more than 140s under the two coupling modes. During cold start phase, under the coupling mode of PNA+EHC+DOC+SDPF+SCR, the conversion efficiencies of carbon monoxide (CO), total hydrocarbons (THC) and nitrogen oxides (NOx) were 97.58%, 94.62% and 78.81% respectively, compared with EHC off, it had increased by 55.84%, 55.84% and 55.84% respectively. Under the coupling mode of PNA+DOC+EHC+SDPF+SCR, the conversion efficiencies of CO, THC and NOx were 58.68%, 87.50% and 95.42% respectively, compared with EHC off, it had increased by 15.91%, 11.70% and 51.41% respectively. EHC coupled front DOC was more conducive to CO and THC emission control, and EHC coupled rear DOC was more conducive to NOx emission control. The SDPF pressure drop corresponding to EHC coupled front DOC was greater than that of EHC coupled rear DOC, the PN conversion efficiency of EHC coupled front or rear DOC was more than 99%.

The security of new energy vehicle (NEV) industry chains has become a strategic issue for industrial competitiveness, the energy transition, and economic security. This study examines how digital economy capabilities jointly support NEV industry chain security across 30 provincial-level administrative regions in China. Drawing on Organizational Information Processing Theory and Dynamic Capability Theory, we conceptualize artificial intelligence capability (AIC), big data analytics capability (BDA), cloud computing infrastructure (CCI), and blockchain application level (BCL) as complementary information-processing and reconfiguration capabilities. We combine Necessary Condition Analysis (NCA), fuzzy-set Qualitative Comparative Analysis (fsQCA), and Random Forest/SHAP analysis. The revised results show that AIC is a practically necessary condition for supply chain resilience, BDA is a necessary condition for achieving a high cybersecurity level, and BCL is a dimension-specific necessary condition for data security. Four sufficient configurational paths—technology-driven, data-driven, infrastructure-driven, and security-synergistic—lead to high comprehensive NEV industry chain security. Robustness checks using alternative calibration anchors and consistency thresholds show that the core configurations are stable. A revised machine learning specification using only digital economy predictors confirms the high relative importance of AIC. It also shows that the marginal contribution of AIC tends to flatten beyond the upper-middle range. The findings provide a configurational and regionally differentiated perspective on digital economy empowerment while avoiding overgeneralization beyond the Chinese provincial context.

The generation of guided trajectories for autonomous vehicles in multi-vehicle interaction scenarios remains challenging because surrounding vehicles continuously adapt their actions under uncertainty. This paper proposes a game-theoretic reinforcement learning (GT-RL) framework that combines a posterior-weighted rolling-horizon local game with proximal policy optimization (PPO) trajectory refinement. The revision makes the incomplete-information cost explicit through a normalized Bayesian posterior, a posterior expected cost, and a certainty-equivalent numerical approximation used by the SQP best-response solver. Using the supplied run-level logs (500 runs per method and scenario), GT-RL achieved mean safety scores of 94.1% (95% bootstrap CI: 93.91–94.28) in the intersection scenario and 91.5% (91.33–91.66) in the highway-merging scenario, with zero collisions in both sets of 500 runs. Paired comparisons with DQN, PPO, MPC-only, and potential-field baselines were significant after Holm correction (p < 0.001) for safety, traversal time, and comfort; DQN and PPO were faster in some cases but had lower safety and comfort. At the intersection, the rule-based method had higher safety but required 4.2 s more traversal time and had a 7.8-point lower comfort score than GT-RL. The findings support game-theoretic reasoning as a strategic prior for local interaction-aware trajectory generation. Claims are restricted to the tested low-to-moderate-speed, non-limit-handling simulations; high-fidelity vehicle dynamics and empirical large-scale timings remain areas of future study.

Reconfigurable robots that alternate between compact rolling-related configurations and legged locomotion require feedback that is both observable and timely enough to supervise morphology changes. This study characterizes a spherical hexapod with 30 ZX20D serial-bus servos and one S80 center-of-mass (COM) shift actuator using the submitted 12.00 s synchronized record spanning HOME, FOLD, three COM-shift states, UNFOLD, and alternating tripod gait. Recalculation from the supplied 30-servo command/feedback archive yields statewise aggregate tracking RMSE values of 1.12–2.29 deg. The largest instantaneous errors are 33.51 deg at ROLL3-UNFOLD and 32.25 deg at a GAITB reversal. Under the timing assumptions, a modeled 30-servo scan requires 26.70 ms and corresponds to a nominal upper scan rate of 37.45 Hz. COM offsets of 72, 66, and 60 mm correspond to dominant-axis attitude peaks of 24.25, 21.55, and 20.02 deg. The uncalibrated contact/load-proxy channels separate the commanded stance and swing groups by a 53.0:1 mean ratio in this record. The resulting evidence is intended to define measurable prerequisites for prospective closed-loop supervision.