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The purpose of this paper is to design an improved parallel regenerative braking system (IPRBS) for electric vehicles (EVs) that increases energy recovery with a constant brake pedal feel (BPF).

The conventional hydro-mechanical braking system is redesigned by incorporating a reversing linear solenoid (RLS) and allowed to work in parallel with a regenerative brake. A braking algorithm is proposed, and correspondingly, a control system is designed for the IPRBS for its proper functioning, and a mathematical model is formulated considering vehicle drive during braking. The effectiveness of IPRBS is studied by analyzing two aspects of regenerative braking (BPF and regenerative efficiency) and the impact of regenerative braking contribution to range extension and energy consumption reduction under European Union Urban Driving Cycle (ECE).

IPRBS is found to maintain a constant BPF in terms of deceleration rate vs pedal displacement during the entire braking period irrespective of speed change and deceleration rate. The regenerative ratio of IPRBS is found to be high compared with conventional parallel regenerative braking, but it is quite the same at high deceleration.

A constant BPF is achieved by introducing an RLS between the input pushrod and booster input rod with appropriate controller design. Comparative analysis of energy regenerated under different regenerative conditions establishes the originality of IPRBS. An average contribution ratio to energy consumption reduction and driving range extension of IPRBS in ECE are obtained as 18.38 and 22.76, respectively.

The paper aims to identify a suitable generic brake force distribution ratio (β) corresponding to optimal brake design attributes in a diminutive driving range, where road conditions do not exhibit excessive variations. This will intend for an appropriate allocation of brake force distribution (BFD) to provide dynamic stability to the vehicle during braking.

Two techniques are presented (with and without wheel slip) to satisfy both brake stability and performance while accommodating variations in load sharing and road friction coefficient. Based on parametric optimization of the design variables of hydraulic brake using evolutionary algorithm, taking into account both the laden and unladen circumstances simultaneously, this research develops an improved model for computing and simulating the BFD applied to commercial and passenger vehicles.

The optimal parameter values defining the braking system have been identified, resulting in effective β = 0.695 which enhances the brake forces at respective axles. Nominal slip of 3.42% is achieved with maximum deceleration of 5.72 m/s² maintaining directional stability during braking. The results obtained from both the methodologies are juxtaposed and assessed governing the vehicle stability in straight line motion to prevent wheel lock.

Optimization results establish the practicality, efficacy and applicability of the proposed approaches. The findings provide valuable insights for the design and optimization of hydraulic drum brake systems in modern automobiles, which can lead to safer and more efficient braking systems.

The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.

The purpose of this paper is to explore the tendencies of liquid consumption in Muslim communities and analyse its impact on Muslims’ consumption practices from the holistic perspective. Liquid consumption refers to a transient and less-materialised mode of consumption that requires both minimal attachment to possessions and hybrid ownership.

This is a conceptual paper that is based on the distinction between Islam as a holistic perspective and Islamic practice as it is applied in different contexts and situations. The Continual Drift Adjustment (CDA) framework of Muslim consumers’ behaviour is developed to be deployed as an analysis framework.

The CDA framework maintains that some problematic cases of Muslim consumption behaviours indicate the drift towards disbalance. Depending on their nature, liquid consumption practices can have different impacts on the drift. Liquid consumption practices underscored by instrumental dissemblance, intellectual insecurity and spiritual scepticism intensify the drift, whereas the incorporation of spiritual sincerity, faithful submission and existential gratefulness into practices and behaviour helps to attenuate the drift.

This research contributes to the theory of liquid consumption by incorporating the religious perspective. Liquid consumption in Islam is a complex area of research, specifically considering the ambivalent meanings of liquidity in Islamic thought.

Marketers of liquid consumption solutions must be aware of these offerings’ double-edged impact on the well-being of Muslim communities. Muslim consumers should be guided towards spiritual sincerity, faithful submission and existential gratefulness in the best way possible, although it must be noted that the customary techniques of marketing would lean towards stimulating the disbalance.

This research is unique because it deals with a topic that has not been researched in the Islamic marketing discipline to this date.

This study aims to investigate the fatigue crack propagation behavior of SiC particle-reinforced 2124 Al alloy composites under constant amplitude axial loading at a stress ratio of R = 0.1. For this purpose, it is performed experiments and comparatively analyze the results by producing 5, 10, 15 Vol.% SiCp-reinforced composites and unreinforced 2124 Al alloy billets with powder metallurgy (PM) production technique.

With the PM production technique, SiCp-reinforced composite and unreinforced 2124 Al alloy billets were produced at 5%, 10%, 15% volume ratios. After the produced billets were extruded and 5 mm thick plates were formed, tensile and fatigue crack propagation compact tensile (CT) samples were prepared. Optical microscope examinations were carried out to determine the microstructural properties of billet and samples. To determine the SiC particle–matrix interactions due to the composite microstructure, unlike the Al alloy, which affects the crack initiation life and crack propagation rate, detailed scanning electron microscopy (SEM) studies have been carried out.

Optical microscope examinations for the determination of the microstructural properties of billet and samples showed that although SiC particles were rarely clustered in the Al alloy matrix, they were generally homogeneously dispersed. Fatigue crack propagation rates were determined experimentally. While the highest crack initiation resistance was achieved at 5% SiC volume ratio, the slowest crack propagation rate in the stable crack propagation region was found in the unreinforced 2124 Al alloy. At volume ratios greater than 5%, the number of crack initiation cycles decreases and the propagation rate increases.

As a requirement of damage tolerance design, the fatigue crack propagation rate and fatigue behavior of materials to be used in high-tech vehicles such as aircraft structural parts should be well characterized. Therefore, safer use of these materials in critical structural parts becomes widespread. In this study, besides measuring fatigue crack propagation rates, the mechanisms causing crack acceleration or deceleration were determined by applying detailed SEM examinations.

The purpose of this paper is to solve the problem that mobile robots are still based on reactive collision avoidance in unknown dynamic environments leading to a lack of interaction with obstacles and limiting the comprehensive performance of mobile robots. A dynamic window approach with multiple interaction strategies (DWA-MIS) is proposed to solve this problem.

The algorithm firstly classifies the moving obstacle movement intention, based on which a rule function is designed to incorporate positive incentives to motivate the robot to make correct avoidance actions. Then, the evaluation mechanism is improved by considering the time cost and future information of the environment to increase the motion states. Finally, the optimal objective function is designed based on genetic algorithm to adapt to different environments with time-varying multiparameter optimization.

Faced with obstacles in different states, the mobile robot can choose a suitable interaction strategy, which solves the limitations of the original DWA evaluation function and avoids the defects of reactive collision avoidance. Simulation results show that the algorithm can efficiently adapt to unknown dynamic environments, has less path length and iterations and has a high comprehensive performance.

A DWA-MIS is proposed, which increases the interaction capability between mobile robots and obstacles by improving the evaluation function mechanism and broadens the navigation strategy of DWA at a lower computational cost. After real machine verification, the algorithm has a high comprehensive performance based on real environment and provides a new idea for local path planning methods.

This study aims to investigate the relationships between loan growth, loan losses and net income after the 2008 global financial crisis. This study further conducts a comparative analysis by considering the period of COVID-19.

This study uses panel data models such as one-step system GMM, random effects, fixed effects and OLS, with a data set of 131 Chinese commercial banks from 2009 to 2020.

The study finds no significant relationship between loan growth and future loan losses. However, after adjusting loan loss by net interest income (NII-adjusted loan loss), the study reveals that loan growth in the subsequent year decreases if NII-adjusted loan loss increases. The study also demonstrates the positive effect of loan growth on net income as newly expanded loans are funded at similar costs but offered at a lower rate compared with existing loans. During COVID-19, loan growth and net income were higher than in previous years.

The findings suggest that Chinese banks can increase lending to support the economy without sacrificing loan quality, emphasizing the importance of maintaining and enhancing credit policies and practices. Chinese banks should also continue to refine their pricing strategies for loans and deposits. The findings also imply that China's policy responses to the impact of COVID-19 could serve as lessons for future policy decisions.

The purpose of this study is to develop a 3D wheel-rail adhesion model under wet condition, which considers the generated surface roughness topography and the traditional braking procedure for high-speed trains.

Wheel-rail adhesion has an important effect on the braking ability of railway vehicle. Based on the deterministic mixed lubrication approach, the model was solved to get the adhesion characteristics of the train during braking. The elastic deformation was calculated with the discrete convolution and fast Fourier transform method. The simulation results of adhesion coefficient were compared with the experimental values. The wheel-rail adhesion characteristics of train braking at several different initial speeds were investigated. The effects of the time-step length and roughness orientation on the contact load ratio were also discussed.

The results show that the adhesion coefficient of the numerical model is in good agreement with the experimental results. At the instant of braking, the adhesion coefficient drops to a lower adhesion level, the value of adhesion coefficient is lower than 0.06, especially at a higher speed (200, 300 and 400 km/h).

It can provide a better understanding of the low adhesion phenomenon of train braking under wet condition.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0040/

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.