Can hydrogen be the sustainable fuel for mobility in India in the global context?

This article provides a critical assessment of H₂ from the standpoint of more widespread use as a sustainable fuel for Indian mobility applications in the global context. The potential techno-economic advantages of utilizing H₂ for automobiles rather than battery electric vehicles or conventional internal combustion engine vehicles are emphasized. The present assessment demonstrates that H₂ production, storage, and distribution costs are the primary challenges, and a significant improvement is still necessary for H₂ to compete either against the internal combustion engine vehicle or the battery electric vehicle to win the race, arguably. The secondary challenges have also been demonstrated, which include the cost of the fuel cell stack and the modifications associated with internal combustion engine vehicles, as well as regulatory and safety concerns, which impede the widespread usage of H₂. It is critical that policy-making for sustainable mobility in India is possible with the aid of a National H₂ Energy Road-Map. This in turn can achieve a cost target of $0.5/kg for H₂.     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.     

A terrain risk assessment method for military surveillance applications for mobile assets

This study proposes an analytical and flexible terrain risk assessment method for military surveillance applications for mobile assets. Considering the risk as the degree of possibility of insurgent presence, the assessment method offers an efficient evaluation of risk in the surrounding terrain for military combat operating posts or observation posts. The method is designed for unmanned aerial vehicles as the surveillance assets of choice to improve the effectiveness of their use. Starting with the area map and geographical data, the target terrain is first digitized for space representation. Then the data of nine geographical parameters are used to formulate five contributing risk factors. These factors are incorporated in an analytical framework to generate a composite map with risk scores that reveal the potential high-risk spots in the terrain. The proposed method is also applied to a real-life case study of COP Kahler in Afghanistan, which was a target for insurgent attacks in 2008. The results confirm that when evaluated with the developed method, the region that the insurgents used to approach COP Kahler has high concentration of high-risk cells.     

Assessing the cost-effectiveness of electric vehicles in European countries using integrated modeling

Electric vehicles (EVs) are considered alternatives to internal combustion engines due to their energy efficiency and contribution to CO₂ mitigation. The adoption of EVs depends on consumer preferences, including cost, social status and driving habits, although it is agreed that current and expected costs play a major role. We use a partial equilibrium model that minimizes total energy system costs to assess whether EVs can be a cost-effective option for the consumers of each EU27 member state up to 2050, focusing on the impact of different vehicle investment costs and CO₂ mitigation targets. We found that for an EU-wide greenhouse gas emission reduction cap of 40% and 70% by 2050 vis-à-vis 1990 emissions, battery electric vehicles (BEVs) are cost-effective in the EU only by 2030 and only if their costs are 30% lower than currently expected. At the EU level, vehicle costs and the capability to deliver both short- and long-distance mobility are the main drivers of BEV deployment. Other drivers include each state’s national mobility patterns and the cost-effectiveness of alternative mitigation options, both in the transport sector, such as plug-in hybrid electric vehicles (PHEVs) or biofuels, and in other sectors, such as renewable electricity.     

Life cycle cost analysis of alternative vehicles and fuels in Thailand

High crude oil prices and pollution problems have drawn attention to alternative vehicle technologies and fuels for the transportation sector. The question is: What are the benefits/costs of these technologies for society? To answer this question in a quantitative way, a web-based model (http://vehiclesandfuels.memebot.com) has been developed to calculate the societal life cycle costs, the consumer life cycle costs and the tax for different vehicle technologies. By comparing these costs it is possible to draw conclusions about the social benefit and the related tax structure. The model should help to guide decisions toward optimality, which refers to maximum social benefit. The model was applied to the case of Thailand. The life cycle cost of 13 different alternative vehicle technologies in Thailand have been calculated and the tax structure analyzed.     

Safe and effective navigation of autonomous robots in hazardous environments

The development of autonomous mobile machines to perform useful tasks in real work environments is currently being impeded by concerns over effectiveness, commercial viability and, above all, safety. This paper introduces a case study of a robotic excavator to explore a series of issues around system development, navigation in unstructured environments, autonomous decision making and changing the behaviour of autonomous machines to suit the prevailing demands of users. The adoption of the Real-Time Control Systems (RCS) architecture (Albus, 1991) is proposed as a universal framework for the development of intelligent systems. In addition it is explained how the use of Partially Observable Markov Decision Processes (POMDP) (Kaelbling et al., 1998) can form the basis of decision making in the face of uncertainty and how the technique can be effectively incorporated into the RCS architecture. Particular emphasis is placed on ensuring that the resulting behaviour is both task effective and adequately safe, and it is recognised that these two objectives may be in opposition and that the desired relative balance between them may change. The concept of an autonomous system having “values” is introduced through the use of utility theory. Limited simulation results of experiments are reported which demonstrate that these techniques can create intelligent systems capable of modifying their behaviour to exhibit either ‘safety conscious’ or ‘task achieving’ personalities.     

An articulated geometry for skid tractor AGVs

An articulated geometry which overcomes the problem of loss of traction in differentially steered skid tractor automatic guided vehicles is described.     

Design and evaluation of an active electromechanical wheel suspension system

This paper presents an electromechanical wheel suspension, where the upper arm of the suspension has been provided with an electric levelling and a damper actuator, both are allowed to work in a fully active mode. A control structure for the proposed suspension is described. The complex design task involving the control of the electric damper and its machine parameters is tackled by genetic optimisation. During this process, these parameters are optimised to keep the power dissipation of the electric damper as low as possible, while maintaining acceptable comfort and road-holding capabilities. The results of the evaluations carried out demonstrate that the proposed suspension can easily adopt its control parameters to obtain a better compromise of performance than that offered by passive suspensions. If the vehicle is to maintain acceptable performance during severe driving conditions, the damper has to be unrealistically large. However, if the electric damper is combined with a hydraulic damper, the size of the electric damper is significantly reduced. In addition, the design of the electric damper with the suggested control structure, including how it regenerates energy, is discussed.     

Energy storage devices for future hybrid electric vehicles

Powertrain hybridization as well as electrical energy management are imposing new requirements on electrical storage systems in vehicles. This paper characterizes the associated vehicle attributes and, in particular, the various levels of hybrids. New requirements for the electrical storage system are derived, including: shallow-cycle life, high dynamic charge acceptance particularly for regenerative braking and robust service life in sustained partial-state-of-charge usage. Lead/acid, either with liquid or absorptive glass-fibre mat electrolyte, is expected to remain the predominant battery technology for 14 V systems, including micro-hybrids, and with a cost-effective battery monitoring system for demanding applications. Advanced AGM batteries may be considered for mild or even medium hybrids once they have proven robustness under real-world conditions, particularly with respect to cycle life at partial-states-of-charge and dynamic charge acceptance. For the foreseeable future, NiMH and Li-ion are the dominating current and potential battery technologies for higher-functionality HEVs. Li-ion, currently at development and demonstration stages, offers attractive opportunities for improvements in performance and cost. Supercapacitors may be considered for pulse power applications. Aside from cell technologies, attention to the issue of system integration of the battery into the powertrain and vehicle is growing. Opportunities and challenges for potential “battery pack” system suppliers are discussed.     

Intelligent tool wear monitoring based on parallel residual and stacked bidirectional long short-term memory network

Effective tool wear monitoring (TWM) is essential for accurately assessing the degree of tool wear and for timely preventive maintenance. Existing data-driven monitoring methods mainly rely on complex feature engineering, which reduces the monitoring efficiency. This paper proposes a novel TWM model based on a parallel residual and stacked bidirectional long short-term memory (PRes–SBiLSTM) network. First, a parallel residual network (PResNet) is used to extract the multi-scale local features of sensor signals adaptively. Subsequently, a stacked bidirectional long short-term memory (SBiLSTM) network is used to obtain the time-series features related to the tool wear characteristics. Finally, the predicted tool wear value is outputted through a fully connected network. A smoothing correction method is applied to improve the prediction accuracy. The proposed model is experimentally verified to have a high prediction accuracy without sacrificing its generalization ability. A TWM system framework based on the PRes–SBiLSTM network is proposed, which has a certain reference value for TWM in actual industrial environments.