Total Cost Of Ownership Research Articles

Modeling the Market-Driven Composition of the Passenger Vehicle Market during the Transition to Electric Vehicles

The automotive market is currently shifting away from traditional vehicles reliant on internal combustion engines, favoring battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs). The widespread acceptance of these vehicles, especially without government subsidies, hinges on market dynamics, particularly customers opting for vehicles with the lowest overall cost of ownership. This paper aims to model the total cost of ownership for various powertrains, encompassing conventional vehicles, HEVs, PHEVs, and BEVs, focusing on both sedans and sports utility vehicles. The modeling uses vehicle dynamics to approximate the fuel and electricity consumption rates for each powertrain. Following this, the analysis estimates the purchase cost and the lifetime operational cost for each vehicle type, factoring in average daily mileage. As drivers consider vehicle replacements, their choice tends to lean towards the most economical option, especially when performance metrics (e.g., range, acceleration, and payload) are comparable across the choices. The analysis seeks to determine the percentage of drivers likely to choose each vehicle type based on their specific driving habits. Advances in battery technology will reduce the battery weight and cost; further, the cost of electricity will decrease as more renewable energy sources will be integrated into the grid. In turn, the total cost of ownership will decrease for the electrified vehicles. By following battery trends, this study is able to model the makeup of the automotive market over time as it transitions from fossil-fuel based vehicles to fully electric vehicles. The model finds until the cost of batteries and electricity is significantly reduced, the composition of the vehicle market is a mixture of all vehicle types.

An integrated Optimization Model of Product Mix, Assortment Packing, and Distribution in A Fashion Footwear Company

Recognizing the paramount importance of operational effectiveness and resource management in supply chain management (SCM) of the fashion industry, this study addresses a specific challenge faced by a prominent Indonesian fashion footwear company. The inefficiency is due to repetitive sorting and packaging processes during product distribution, which significantly impact optimal production mixes and product distribution from the distribution center to the point of sale. A crucial aspect is also the optimization of the delivery route. To address these challenges and minimize the total cost of ownership, the study proposes an integrated optimization model. This model simultaneously determines the optimal production quantity, assortment packaging, and distribution channels, taking into account decision variables related to distribution in configuration boxes, overload and underload products, as well as production numbers that respond to store-specific demand fluctuations. A notable contribution of this research is the integration of product mix decisions into the assortment packaging and distribution model, which represents a novel approach. The optimal solution determined using the LINGO 18.0 software highlights the significant influence of product penalty costs and product demand parameters on the objective function, while shipping costs have no noticeable influence. By emphasizing the integration of product mix decisions into the optimization framework, this research contributes significantly to improving the understanding and practical application of efficient supply chain management in the fashion industry.

The impact of financial incentives on the total cost of ownership of electric light commercial vehicles in EU countries

Many EU countries have used financial incentives to promote electric light commercial vehicles and decarbonise urban freight transport. However, the high costs of electric light commercial vehicles still pose a significant adoption barrier. This paper evaluates the impact of financial incentives on the total cost of ownership of electric light commercial vehicles in the European Union and their role in achieving the cost-competitiveness of electric vehicles. A pairwise comparison is performed for three weight categories of electric and diesel vehicles in twelve countries. Our analysis shows that financial incentives have a high impact on the total cost of ownership and have proven necessary to achieve electric vehicles' cost-competitiveness in most cases. However, in specific cases, financial incentives may no longer be needed as the cost of electric vehicles' ownership would have been lower than diesel vehicles even without them. This paper demonstrates the importance of adjusting government incentives to avoid unnecessary funding allocations while promoting the decarbonisation of light commercial vehicles, particularly as the number of incentives does not directly correlate with electric vehicles penetration.

New Approach Towards Sustainability – The Global Efficiency Concept (GEff)

In the actual economical environment, business sustainability requires high-efficiency technological processes and new innovative developments. That is why the efficiency concept has to be present at all levels of industrial and financial activities. The proposed concepts in this paper could be further developed as a model for improving companies’ corporate energy policies.
 Nowadays, some purchase decisions for equipment are still driven predominately by the purchase price, and the full consequences of energy efficiency and the impact on the environment are not always considered.
 In general relatively “low value equipment” purchase policy is still driven by purchase price only, in spite of the evidence that such price represents a maximum of 5 % to 7 % of the total expenses related to the total costs of ownership. In the minerals industry “low value equipment”, like low-voltage motors (up to 1100 volts, 50/60 Hz), are found many times and in very large numbers, their efficiency and reliability influencing dramatically specific costs of technological processes.
 Although with “major equipment” energy savings are considered more in the purchase decision, every growing importance on the environment of “Green House Gas” (GHG) emissions is still not a major factor when selecting equipment. Often more traditional equipment is purchased at the expense of new innovative technologies that in addition to providing energy savings can also be used as a tool for trading Carbon Credits in the financial marketplace. An example of such a technology is the IsaMill™ comminution machine, which is becoming more widely used in gold and general mining operations in South Africa and throughout the world. Comminution in the mining industry is one of the most energy intensive activities in the world, and the innovative use of “major equipment” saving power can also have a positive effect on the environment.
 The paper presents descriptions of the essentials of the Global Efficiency (GEff) concept that has been promoted over the last years in South Africa. Price-efficiency criteria (as a corollary of GEff) are investigated for applications incorporating equipments that are driven by low and high voltage motors.
 The paper presents theoretical and technical aspects analysing the economic and environmental impact, by reducing total cost of ownership with energy savings, for one “low value equipment” in typical applications largely used in mineral processing in the gold mining industry, and one “major equipment” purchase at a current operating gold mine where the innovative IsaMill™ comminution technology was installed as an alternative to traditional older technologies.
 Besides the impact of energy savings with high-efficiency technological processes and new innovative developments, this paper suggests the general impacts of:
 
 Technical and economical performance improvements and competitiveness of mining corporations to international standards;
 Defusing incipient energy crisis in the gold mining sector;
 Improving environmental conditions;
 Creating new job opportunities in the gold mining sector.

Battery Electric Buses or Fuel Cell Electric Buses? A Decarbonization Case Study in the City of Brescia, Italy

Nowadays, designing and adopting sustainable and greener transport systems is of upmost interest. The European Commission and different EU countries are developing plans and programs—but also delivering resources—aimed at the decarbonization of cities and transport by 2030. In this paper, the case study of the city of Brescia, a city of about 200,000 inhabitants located in northern Italy, is addressed. Specifically, a preliminary operational and financial feasibility study is performed assuming the replacement of the entire compressed natural gas (CNG) powered bus fleet of a specific line; the two alternatives considered are battery electric buses (BEBs) and fuel cell electric buses (FCEBs). For the comparison and evaluation of the two alternatives, specific economic parameters of the three alternatives (BEB, FCEB and the current solution CNGB) were considered: CAPEX (CAPital EXpenditure) and OPEX (OPerational EXpenditure). This allowed us to determine the TCO (total cost of ownership) and TCRO (total cost and revenues of ownership) along three annuities (2022, 2025 and 2030). For the BEB alternative, the TCO and TCRO values are between EUR 0.58/km and EUR 0.91/km. In the case of the FCEB solution, the values of TCO and TCRO are between EUR 1.75/km and EUR 2.15/km. Considering the current CNGB solution, the TCO and TCRO values range between EUR 1.43/km and EUR 1.51/km.

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

A total cost of ownership analysis of zero emission powertrain solutions for the heavy goods vehicle sector

Transport-related activities represented 34% of the total carbon emissions in the UK in 2022 and heavy-duty vehicles (HGVs) accounted for one-fifth of the road transport greenhouse gas (GHG) emissions. Currently, battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (FCEVs) are considered as suitable replacements for diesel fleets. However, these technologies continue to face techno-economic barriers, creating uncertainty for fleet operators wanting to transition away from diesel-powered internal combustion engine vehicles (ICEVs). This paper assesses the performance and cost competitiveness of BEV and FCEV powertrain solutions in the hard-to-abate HGV sector. The study evaluates the impact of battery degradation and a carbon tax on the cost of owning the vehicles. An integrated total cost of ownership (TCO) model, which includes these factors for the first time, is developed to study a large retailer's HGV fleet operating in the UK. The modelling framework compares the capital expenditures (CAPEX) and operating expenses (OPEX) of alternative technologies against ICEVs. The TCO of BEVs and FCEVs are 11% to 33% and 37% to 78% higher than ICEVs; respectively. Despite these differences, by adopting a longer lifetime for the vehicle it can effectively narrow the cost gap. Alternatively, cost parity with ICEVs could be achieved if BEV battery cost reduces by 56% or if FCEV fuel cell cost reduces by 60%. Besides, the pivot point for hydrogen price is determined at £2.5 per kg. The findings suggest that BEV is closer to market as its TCO value is becoming competitive, whereas FCEV provides a more viable solution than BEV for long-haul applications due to shorter refuelling time and lower load capacity penalties. Furthermore, degradation of performance in lithium-ion batteries is found to have a minor impact on TCO if battery replacement is not required. However, critical component replacement and warranty can influence commercial viability. Given the high costs, we propose financial incentives and vehicle tax reforms to reduce costs of critical components that will encourage the roll-out of zero emission HGVs.

Data-driven Analysis of the Cost-Performance Trade-off of Reconfigurable Intelligent Surfaces in a Production Network

This paper presents a comprehensive study on the deployment of Reconfigurable Intelligent Surfaces (RIS) in urban environments with poor radio coverage. We focus on the city of London, a large metropolis where radio network planning presents unique challenges due to diverse geographical and structural features. Using crowd-sourced datasets, we analyze the Reference Signal Received Power (RSRP) from end-user devices to understand the existing radio coverage landscape of a major Mobile Network Operator (MNO). Our study identifies areas with poor coverage and proposes the deployment of RIS to enhance signal strength and coverage. We selected a set of potential sites for RIS deployment and, combining data from the MNO, data extracted from a real RIS prototype, and a ray-tracing tool, we analyzed the gains of this novel technology with respect to deploying more conventional technologies in terms of RSRP, coverage, and cost-efficiency. To the best of our knowledge, this is the first data-driven analysis of the cost-efficiency of RIS technology in the production of urban networks. Our findings provide compelling evidence about the potential of RIS as a cost-efficient solution for enhancing radio coverage in complex urban mobile networks. More specifically, our results indicate that large-scale RIS technology, when applied in real-world urban mobile network scenarios, can achieve 72% of the coverage gains attainable by deploying additional cells with only 22% of their Total Cost of Ownership (TCO) over a 5-year timespan. Consequently, RIS technology offers around 3x higher cost-efficiency than other more conventional coverage-enhancing technologies.

Projections of the costs of medium- and heavy-duty battery-electric and fuel cell vehicles (2020-2040) and related economic issues

This study investigates the economic viability of various medium- and heavy-duty battery-electric and hydrogen fuel cell vehicles compared to their diesel equivalents from 2020 to 2040. Using the ADVISOR simulation program, performance and energy consumption were evaluated under unique road, load, and design parameters, adjusted for projected technological advancements. The initial cost, total cost of ownership (TCO), and payback periods were calculated for each vehicle class over 5-year and 15-year periods. Notably, due to technology cost reductions, both battery-electric and fuel cell vehicles witness significant cost decreases between 2020 and 2030 and a slower reduction from 2030 to 2040. Given stable electricity prices, declining hydrogen prices, and slightly rising diesel prices, the TCO of electrified trucks typically undercuts diesel trucks before their purchase costs align. By 2025, most battery-electric trucks achieve TCO competitiveness, with payback periods reducing to <4 years by 2030. However, fuel cell vehicles face longer payback periods due to high hydrogen fuel costs. By 2030, if hydrogen cost falls below $7/kg, fuel cell trucks can achieve 3–5-year payback periods, and fuel cell buses can recoup costs within a year. By 2030, both battery-electric and hydrogen fuel cell trucks are expected to be competitively priced against diesel vehicles, assuming a continued decrease in battery and fuel cell costs coupled with moderate electricity and hydrogen prices. Sensitivity analysis confirmed the robustness of these conclusions despite reasonable fluctuations in major cost variables.

Cost-efficient cooling of buildings by means of geothermal borefields with active and passive cooling

Due to the increasing demand for space heating and cooling and emphasis on sustainable solutions, ground source heat exchangers become more attractive. However, ground source heat pumps using direct cooling face adoption challenges due to their high upfront investment costs. These costs can be reduced by limiting the required borefield size through combining active and passive cooling regimes with ground source heat pumps. The absence of a widely-available sizing methodology for combined cooling regimes results in suboptimal borefield design. Hence, the full economic potential of combining these systems is not utilised. Therefore, this study introduces an innovative approach for cost-efficient borefield sizing that integrates active and passive cooling during the design phase, aiming for minimal TCO. The methodology is based on a doubly iterative sizing algorithm using an hourly time resolution. Novel to this domain, it relies on Bayesian optimisation to determine the most cost-efficient borefield size. It shows that load profiles constrained by maximum temperature limits in passive cooling configurations or those characterised by significant cooling demand peaks exhibit substantial potential benefits from a combined active and passive cooling approach. Real-world case studies further validate our approach, demonstrating achievable total cost of ownership (TCO) savings of 35% and 33% when optimising the integration of active cooling, compared to traditional passive cooling methods. To facilitate further research and industry applications, the algorithm has been integrated into the open-source software GHEtool.

EMI Shielding for System in Package Using Spray Coating and Silver Particle-Free Ink

There is a constant drive to pack electronics into smaller spaces. Recently, IoT devices such as smart watches, wearables and other connectivity devices have been major drivers of further miniaturization and spurred System in Package ‘SIP’ innovations. SIP enables several integrated circuits (ICs) along with larger capacitors/inductors to be housed in one package. Many of these ICs operate at radio frequencies and the proximity increases electromagnetic interference (EMI). The traditional solution of soldering a ‘metal can’ is not feasible. On the other hand, 5G enabled devices and high frequency communication electronics require shielding well beyond RF, typically 5 ? 25 GHz and beyond. Compartmental and conformal shielding of the package is necessary and sputtered metal has typically been utilized to provide the shield. The traditional sputtering method is a Physical Vapor Deposition process (PVD) that involves vaporizing a metal and depositing it onto the surfaces of the components. PVD is currently the most commonly used method to apply the EMI shield and it requires a complex, multi-step process. Alternatively, the technology is seeing a shift to sprayable or jettable conductive-based ink conformal shielding. This approach brings about substantial total cost of ownership and UPH/throughput advantages as the ink-based processes (spray/jet) does not require vacuum, and relatively low temperatures (at or below 180C in most cases). From a technology perspective, ink-based approaches have the advantage in shielding complex 3D, non line-of-sight packages and electronic module housings, directed (mask-less) shielding with no major drop in shielding performance or REL (reliability) behavior.

Green premium modeling based on total cost ownership analysis: From the Chinese Electric Vehicle sales forecasting perspective

In the field of energy economics, the concept of “green premium” refers to the cost difference between zero-emission or emission-reducing technologies and emission-emitting technologies. This cost difference plays a crucial role in the adoption and commercialization of renewable energy technologies, which is essential for addressing climate change. However, the green premium, as an abstract concept, is often used qualitatively, and research on quantifying the green premium is very limited. This has significant adverse effects on both the formulation of business strategies for companies and the planning of government policies. The Total Cost of Ownership (TCO) method is a widely used cost analysis approach in businesses and organizations. It can quantitatively assess and understand the overall costs associated with specific products, assets, or services, thereby assisting decision-makers in making informed choices and managing resources. Therefore, this study introduces, for the first time, a TCO-based green premium modeling model to address the challenge of quantifying the green premium. Considering that China’s Electric Vehicles (EVs) industry has successfully overcome the green premium barrier and entered the commercialization phase, it is an appropriate domain for studying the green premium. To further demonstrate the effectiveness and scalability of the modeling, this paper enhances the classic Bass model for sales forecasting of electric vehicles. It innovatively incorporates the influence of the green premium in the generalized Bass model. Additionally, the study uses primary data from industry research to construct a multi-factor green premium model for EVs based on TCO analysis. It also develops a generalized Bass diffusion model that considers the green premium and selects time-series data on EV diffusion in the Chinese market from 2010 to 2021. A genetic algorithm is employed to fit the model parameters, and different scenarios are considered to forecast EV market penetration over the next decade. Experimental results validate that incorporating the green premium in the generalized Bass model leads to better forecasting performance compared to methods that do not consider the premium which proved these related green premium modeling approaches exhibit good accuracy and scalability.

Analytical and quantitative assessment of capital expenditures for construction of an aboveground suspended weight energy storage

The capital expenditures to energy capacity ratio (capex) stands as a key competitive metric for energy storage systems. This paper presents an evaluation of this indicator for an aboveground suspended weight energy storage system. For the first time, an analytical foundational correlation was found between capital expenditures of gravity energy storage, its energy capacity, and storage power. The correlation reveals that capex can be expressed as the sum of three components: one inversely proportional to discharge duration, another inversely proportional to the square root of energy capacity, and a constant term. By using established construction and power element prices the study demonstrates that capex can be reduced to less than 600 $/kW·h for discharge durations of 4 h or more, and can decrease to nearly 450 $/kW·h for a 10-h discharge duration. Employing the computed capex an evaluation of the total cost of ownership was conducted and juxtaposed with lithium-ion energy storage. The gains from adopting gravity technology become significant starting from the initial replacement of degraded Li-ion batteries. This scenario results in nearly a twofold savings in the ownership cost of gravity energy storage system over a 20-year operational span with further prospects for enhanced economic benefits.

Sub-segment-based approach for assessing growth and energy transition trajectories of Indian two-wheelers

The transition trajectory of India's two-wheeler (2W) vehicle segment is studied using a sequential modelling framework for projecting sub-segment-wise 2W fleet, energy demand, and associated CO2 emissions. Road density per capita was identified as a more significant explanatory variable than GDP per capita in estimating 2W fleet size in India. The elasticity method was used to evaluate the 2W vehicle saturation level based on five different indirect parameters. It was found that population density had the highest impact (48%), followed by urbanization (31%) and adult population share (16%). The impact of the total cost of ownership was negligible. The mean 2W vehicle saturation level was calculated to be 314 while the ownership was found to be 207, 265, and 297 vehicles per 1000 people by 2030, 2040, and 2050, respectively. Scooters were found to be leading the e-transition of 2Ws but a successful e-transition of India's 2Ws would not be achieved without transitioning the motorcycles. Two motorcycle clusters were identified that offer economies of scale towards e-transitioning. Closer scrutiny of six plausible e-transition scenarios showed that a 50% penetration of E−2Ws is unattainable before 2045. The biggest obstacle in achieving high E−2W penetration in India would be the limited capacity to supply indigenously produced vehicles. A high import dependence on battery technology and critical raw materials would limit the energy transition and diversification of the Indian road transport sector. India should follow the mass adoption-driven diffusion pathway in the short-to-medium term and the affordability-constraint diffusion pathway in the long term to achieve the best results in terms of reduction in energy demand and associated emissions for the 2W segment. The gains from the e-transition of the road transport sector would not be substantial without a simultaneous transition in the country's electricity generation mix away from coal-based thermal power.

Apache Wayang: A Unified Data Analytics Framework

The large variety of specialized data processing platforms and the increased complexity of data analytics has led to the need for unifying data analytics within a single framework. Such a framework should free users from the burden of (i) choosing the right platform( s) and (ii) gluing code between the different parts of their pipelines. Apache Wayang (Incubating) is the only open-source framework that provides a systematic solution to unified data analytics by integrating multiple heterogeneous data processing platforms. It achieves that by decoupling applications from the underlying platforms and providing an optimizer so that users do not have to specify the platforms on which their pipeline should run. Wayang provides a unified view and processing model, effectively integrating the hodgepodge of heterogeneous platforms into a single framework with increased usability without sacrificing performance and total cost of ownership. In this paper, we present the architecture ofWayang, describe its main components, and give an outlook on future directions.

A novel method for co-optimizing battery sizing and charging strategy of battery electric bus fleets: An application to the city of Paris

Battery-electric buses (BEBs) are a promising technology for replacing diesel buses and reducing their environmental burden. However, their charging process can take several hours, depending on the charging technique and strategy, making them susceptible to schedule disruptions. Furthermore, the selection of the charging strategy and battery size can increase the total capital investment and operational expenses of a BEB fleet, which is a major obstacle to its adoption. Therefore, to minimize the total cost of ownership (TCO) and prevent schedule disruptions, it is essential to establish a well-defined approach to determine an appropriate battery size and charging strategy for BEB fleets.This paper presents a method for reducing the TCO of BEB by determining the optimal battery size and charging strategy for each bus while satisfying operating constraints. The method involves a two-step optimization algorithm that uses Dynamic Programming and Genetic Algorithm. The study applies this approach to the bus fleet serving line 21 in Paris and generates the optimal battery sizing, charging strategy, and required charging infrastructure. The results indicate that 100 kWh batteries offer the best trade-off between capital and operational expenditure for the fleet deployment if used with 65–85 kW chargers at bus terminals.

Towards a low-cost sustainable broadband solution in rural areas of low and middle-income countries: Tanzania’s backhaul perspective

Although broadband internet has proven to accelerate the fulfilment of the information and communication for development (ICT4D) agenda, connectivity issues persist in some regions of the world, particularly in rural areas of Low and Middle-Income Countries (LMICs) which host 93% of the unconnected global population. Due to the lack of economic feasibility in these locations for service providers, International Telecommunication Union (ITU) has been advocating for low-cost sustainable solutions in such areas. Among the challenging broadband infrastructure segment seems to be the backhaul (middle-mile) as rural areas are remotely located from the backbone end-points. With Tanzania exemplifying LMICs, this paper presents a Techno-Economic Analysis (TEA) to compare the widely utilized backhaul (Microwave) and the promising Broadband over Power Line (BPL) towards achieving low-cost broadband solutions. To demonstrate technical viability in terms of capacity, Pathloss and MATLAB were utilized from which both technologies demonstrated the broadband-suitably capacity (161Mbps for Microwave and 168.99Mbs for BPL). From economic perspective, the Total Cost of Ownership (TCOs) for both technologies were determined using a Cost Model; BPL fared better as the cost of establishing one microwave link could have established almost 6 BPL links. Apart from adding to the body of knowledge on TEAs involving backhauls, this paper informs policymakers and other related stakeholders on the potential cost-benefit of BPL towards curbing the existing broadband connectivity gap.

Particle Swarm Optimization Method for Stand-Alone Photovoltaic System Reliability and Cost Evaluation Based on Monte Carlo Simulation

In rural regions with limited access to the power grid, self-reliance for electricity generation is paramount. This study focuses on enhancing the design of stand-alone photovoltaic installations (SAPV) to replace conventional fuel generators thanks to the decreasing costs of PV modules and batteries. This study presents a particle swarm optimization (PSO) method for the reliable and cost-effective sizing of SAPV systems. The proposed method considers the variability of PV generation and domestic demand and optimizes the system design to minimize the total cost of ownership while ensuring a high level of reliability. The results show that for the PSO method with 500 iterations, the error is around 2%, and the simulation time is approximately 2.25 s. Moreover, the PSO method allows a much lower number of iterations to be used in the Monte Carlo simulation, with a total of 100 iterations used to obtain the averaged results. The optimization results, encompassing installed power, battery capacity, reliability, and annual costs, reveal the effectiveness of our approach. Notably, our discretized PSO algorithm converges, yielding specific parameters like 9900 W of installed power and a battery configuration of five 3550 Wh units for the case study under consideration. In summary, our work presents an efficient SAPV system design methodology supported by concrete numerical outcomes, considering supply reliability and installation and operational costs.

Robotics Software: Past, Present, and Future

Robotics is powered by software. Software tools control the rate of innovation in robotics research, drive the growth of the robotics industry, and power the education of future innovators and developers. Nearly 900,000 open-source repositories on GitHub are tagged with the keyword robotics—a potentially vast resource, but only a fraction of those are truly accessible in terms of quality, licensability, understandability, and total cost of ownership. The challenge is to match this resource to the needs of students, researchers, and companies to power cutting-edge research and real-world industrial solutions. This article reviews software tools for robotics, including both those created by the community at large and those created by the authors, as well as their impact on education, research, and industry.

Techno‐economic study for the implementation of electric buses for sustainable urban and interurban transportation

AbstractA cleaner transportation sector requires the implementation of a variety of measures, such as the use of electric vehicles. Electric mobility has seen increasing use in public transportation, even though it still faces significant challenges. Electric bus fleets require high‐performance batteries to minimize the cost and weight of the buses. This paper investigates the energy consumption of an electric bus in urban and interurban transit using two methods: forward‐facing and backward‐facing approaches. The obtained findings have shown that the energy consumption of a bus depends on the road and its characteristics, ranging between 0.98 and 1.39 kWh/km. Furthermore, a regenerative braking analysis has been performed, and it has been found that this factor plays a significant role in reducing energy consumption by 21%. Finally, a life cycle assessment and an environmental analysis have been conducted. The obtained results have shown that the total cost of ownership of the buses in this project will be around 1.76 $/km. The use of electric buses could eliminate the greenhouse gas emissions produced by public transportation in the investigated province.