Load fluctuations of high-horsepower tractors impair the smoothness of field operations and challenge the reliability of conventional power shift transmissions. This study presents a TRIZ-based design and experimental validation of a dual-flow coupled hybrid powertrain that replaces power shift technology. Using the TRIZ substance-field (Su-Field) model, we identified the technical and physical contradictions among transmission reliability, load adaptability, and operational smoothness, and resolved them via Altshuller’s contradiction matrix and inventive principles to synthesize the dual-flow coupled configuration. In this configuration, the engine and the generator motor power both the power take-off (PTO) output and the front/rear axle drives through three controllable clutches, enabling four operating modes and split power output. A dynamic simulation model was built for plowing and rotary tillage, and a hardware-in-the-loop (HIL) test platform was established. Simulation and HIL results verify the feasibility of motor torque assist to reproduce power shift characteristics, with reduced gear-shift frequency; split power output decouples implement load fluctuations from the driveline and improves the operational smoothness of rotary tillage under variable loads.
The aim of this scientific study is to investigate the coupled effects of active battery thermal management on temperature regulation, auxiliary cooling energy demand, and long-term degradation-related exposure under a prescribed tropical heat-soak scenario. A reference 50 Ah equivalent lithium-ion cell is represented by a temperature- and state-of-charge-dependent second-order equivalent-circuit model coupled to a two-node core–surface thermal network. The numerical methods include Coulomb counting, irreversible electrical heat generation, proportional cooling control, time integration of normalized degradation-stress indicators, and ambient-temperature and cooling-setpoint sensitivity analyses. A synthetic 3-day charge–discharge duty cycle and a deterministic 28–42 °C ambient-temperature waveform provide repeatable boundary conditions. Relative to passive operation, the modeled active system lowers peak core temperature while incurring additional cooling electricity demand. The setpoint analysis demonstrates a trade-off between thermal protection, auxiliary energy, and normalized degradation exposure. The framework offers a consistent basis for comparative thermal-management assessment; because the reference parameters and exposure relationships are not experimentally calibrated, it does not establish cell-specific capacity fade, service life, or predictive accuracy.
Electric-vehicle (EV) diffusion in large, heterogeneous, and price-sensitive markets such as India cannot be adequately represented by either aggregate diffusion curves or agent-based models (ABMs) in isolation: the former cannot express heterogeneous buyers or shifting policy, and the latter are rarely anchored to a calibrated national diffusion trajectory. This paper develops a dynamic mathematical model of EV adoption among Indian passenger-car buyers that couples a Bass diffusion model at the macro level with an ABM of heterogeneous consumers at the micro level, with both layers driven by a time-varying PESTL (political, economic, social, technological, legal/environmental) representation of the market environment. Unlike earlier hybrid proposals in which the two layers are described together but solved independently, this framework implements a genuine two-way coupling: in every simulated year, 5000 agents positioned on a small-world social network make discrete vehicle-choice decisions based on deterministic utility; the resulting peer-adoption share and the normalised PESTL drivers jointly determine the time-varying innovation coefficient p(t) and imitation coefficient q(t); a bounded Bass equation with a time-varying saturation ceiling then advances the national EV share of new-car sales; and that macro share re-enters the agents’ social-influence term in the following period, closing the loop. The model is anchored on current Indian parameters—a passenger-car EV penetration of approximately 4% in 2025, volumetric battery-pack cost near US$108/kWh, and around 29,000 public charging points—and run under baseline, aggressive-support, and stalled-support scenarios to 2050, together with a 3 × 3 scenario matrix cross-combining three PESTL environments with three agent-population profiles. For the illustrative calibration, the baseline scenario yields approximately 29.5% EV sales share by 2030—narrowly below the Government of India’s 30% target for passenger cars—and approximately 30.4% under the aggressive-support scenario. A formal two-way ANOVA-based variance decomposition, with 10 independent random-seed replications per scenario cell (90 observations in total), indicates that heterogeneous agent characteristics account for 81.3% of the variance in 2030 outcomes, substantially exceeding the 16.8% attributable to the PESTL policy environment, with the remaining 1.9% reflecting interaction and stochastic noise. One-at-a-time sensitivity analysis identifies the peer-influence weight as the parameter with the largest overall effect on 2030 penetration, with the purchase-subsidy multiplier remaining the most effective lever among instruments directly controllable by policy. The emergent Bass coefficients fall within established meta-analytical ranges, providing internal plausibility validation. The framework is offered as a transparent decision-support and scenario-analysis tool for policymakers and industry planners, not as a point forecast of future EV sales.
As battery performance, range, and intelligent features become baseline competitive attributes in China’s new energy vehicle (NEV) market, consumers also encounter brand and model names when forming impressions of vehicles. This study examines whether perceptions of Chinese-character naming are associated with brand attitude, subjective norm, and purchase intention. The stimulus–organism–response (S-O-R) model organizes these proposed associations, with customer-based brand equity theory and the theory of planned behavior serving complementary roles. The case analysis describes the naming architectures associated with six selected Chinese NEV companies and brands; reported sales and delivery series from 2021 to 2025 provide descriptive market context rather than estimates of naming effects; and a survey of 353 respondents examines the proposed associations using confirmatory factor analysis and controlled regressions. In the controlled purchase-intention model, naming semantic clarity, brand attitude, perceived quality, and subjective norm had positive coefficients, whereas perceived risk had a negative coefficient; the model explained 61.3% of the observed variance. Cultural resonance had no significant direct coefficient but had significant specific indirect associations through brand attitude and subjective norm. These cross-sectional findings are consistent with an associational brand-symbol pathway; they do not establish that names cause purchases or sales.
As cities seek to reduce car dependency while maintaining individual accessibility, understanding the economic implications of switching transport modes has become increasingly important for both users and policymakers. This study investigates the total cost of ownership of a speed pedelec as the primary commuting vehicle. By integrating user profiles and one-year longitudinal cost data through 480 data points, this paper calculates the total cost of ownership (TCO) for each of the 13 respondents. Although based on a small sample, the study provides rare empirical insights into real-world speed pedelec ownership costs. The analysis includes costs for maintenance, repairs, accidents, extra costs, and accessories. The one-year TCOs of the 13 respondents are compared with the ownership costs of a small battery electric, mild hybrid, and petrol-powered car. The findings show that an SP may present a cost-competitive mobility option compared with owning a comparable petrol Internal Combustion Engine Vehicle (ICEV), Mild Hybrid Electric Vehicle (MHEV) or Battery Electric Vehicle (BEV). These findings can inform individual mobility choices, help policymakers to develop targeted policy interventions to encourage sustainable and inclusive transport and contribute to discussions on the economic feasibility of alternative mobility configurations.
