Lower Total Cost Of Ownership Research Articles

Case Study: Advanced Technology Underpins Efficiency and Climate-Related Goal Gains

_ Today’s gas-compression operators are under increasing pressure to reduce greenhouse gas (GHG) emissions. Fortunately, multiple technologies are available that can support that objective while enabling operators to move more gas cost-effectively. Embracing such advancements can positively impact a reduced-carbon future without compromising operational efficiency or profitability. To choose the right technologies for a gas-compression package, it’s critical for operators to have a clear understanding of their business and GHG emissions-related goals. Operators also need clarity concerning the impact of evolving requirements on total cost of ownership (TCO) as well as potential financial ramifications. Producing more gas at a lower cost with lower GHG emissions is possible with new technologies. Operators can support their success by choosing the right engine driver for a gas-compression package based on their unique needs and site conditions. It’s critical to consider an engine’s power density and TCO, as that informs an operator’s selections and can lower a gas-compression package’s operating cost in terms of dollars per thousand cubic feet ($/Mcf) of gas throughput. An engine, such as the Cat G3600 A4 Gen 2, that can deliver a 10% power increase compared to the previous model can allow operators to use fewer engines to perform the same amount of work. This advantage can lower capital requirements, reduce operating expenses, and decrease fuel consumption. Fewer engines operating in the field may also contribute to lower GHG emissions. Modernizing Existing Assets Operators prioritize flexibility, durability, and lower TCO. They can support those objectives by choosing an engine platform that allows performance upgrades across the life of the engine. This enables operators to apply advanced technology in their existing fleet year after year without incurring the substantial cost of purchasing a new engine. Engine upgrade kits offer operators an option to maximize and modernize active assets in a streamlined way, as the upgrades can be applied conveniently and cost-effectively at the time of a scheduled overhaul to minimize disruption. For example, by using an upgrade kit for an A4 Gen 1 engine model referenced above, operators can lower volatile organic compounds up to 32%, formaldehyde up to 24%, carbon monoxide up to 13%, methane emissions up to 33%, and total GHG emissions up to 5% on a grams per brake horsepower-hour (g/bhp-hr) basis* while saving the traditional capital expenditure of a new engine. (*Site conditions: Same power level between the G3600 A4 Gen 1 and Gen 2, 85MN, 905 BTU/scf, 100% load, 25°C ambient, 500-ft altitude.) Such updates are relatively cost neutral when applied as part of a scheduled major overhaul and require minimal or no change to the compression package. This makes upgrade kits a wise choice to ensure equipment keeps pace with industry demands.

Practical low-temperature gasoline combustion for very high efficiency off-road, medium- and heavy-duty engines

Low-temperature gasoline combustion (LTGC) with additive-mixing fuel injection (AMFI) is a new combustion strategy that has been demonstrated to deliver 9%–25% better brake thermal efficiency than similar-sized market-leading diesel engines over the operating map. Moreover, the LTGC-AMFI engine shows near-zero smoke, and NOx emissions are 4–100 times lower than those of a diesel, sufficiently low that no aftertreatment, or only passive NOx aftertreatment, would be sufficient (diesel exhaust fluid is not required). LTGC-AMFI combustion is based on kinetically controlled compression ignition of a dilute charge with a variable amount of low-to-moderate fuel stratification. Fast combustion control is provided by adding minute amounts of an ignition-enhancing additive into the fuel each engine cycle to control its reactivity. This strategy was used to operate a medium-duty (MD) LTGC-AMFI engine at loads from idle to 16.3 bar BMEP and speeds from 600 to 2400 rpm with regular E10 gasoline, which covers nearly the entire operating map of a typical MD engine. Turbine-out temperatures were sufficient for an oxidation catalyst to control hydrocarbon and CO emissions. Autonomie simulations over the GEM ARB Transient and the GEM 55 mph Cruise driving cycles for class-6 trucks using this technology showed fuel economies of 8.1 and 11.4 mpg-gasoline-equivalent, respectively, corresponding to 18.6% and 13.4% improvements over a similar-size diesel engine. Engine-out NOx emissions were 0.024 and 0.01 g/bhp-h, respectively, well below current U.S. emission standards. These results show that switching from diesel to LTGC-AMFI engines would greatly reduce greenhouse gas (GHG) emissions for off-road, MD and HD applications, which will continue to rely on combustion engines because electrification is not practical in the foreseeable future. With their reduced fuel consumption, the lower cost of gasoline compared to diesel fuel, and much lower aftertreatment costs, LTGC-AMFI engines also offer a significantly lower total cost of ownership.

Comparative Evaluation of Total Cost of Ownership of Battery-Electric and Diesel Trucks in India

Whereas battery electric vehicles (BEVs) are on their path to maturity in the light-duty segment, their viability in medium- and heavy-duty applications faces greater skepticism. Furthermore, their higher upfront cost relative to diesel trucks is perceived as even more challenging for less wealthy nations such as India. Here, we undertake a total cost of ownership (TCO) assessment of battery electric trucks (BETs) for four different classes of freight trucks in India using a bottom-up vehicle subsystem level cost estimation. We estimate that, in a scenario in which the incremental upfront cost of BETs relative to a diesel truck is simply the extra cost of the battery pack procured at close to current average international battery pack prices, BETs could have lower TCO, less than 5-year payback, and deliver substantial life cycle cost savings, even without accounting for their environmental benefits. In addition to eliminating tailpipe pollution, they already deliver lower life cycle greenhouse gas emissions based on the current average electricity mix in India. Achieving a scale production that yields lower TCO will, however, require public support over a long maturation phase marked by learning-by-doing externalities and lack of economies of scale when BETs will be costlier. Currently, while there exist multiple types of incentive for light-duty BEVs as well as for cell manufacturing in India, targeted policies for zero emissions trucks are absent; this is a gap that needs to be filled if BETs are to emerge as a serious alternative to diesel trucks in a decade or so.

Techno-economics of fiber versus microwave for mobile transport network deployments [Invited

One of the challenges network operators face is designing and deploying cost-efficient transport networks (TNs) to meet the high capacity and strict latency/reliability requirements of today’s emerging services. Therefore, different aspects, including the appropriate technology, the level of reconfigurability, and the functional split option, need to be considered. A crucial aspect of network design is assessing the impact of these factors against the total cost of ownership (TCO), latency, and reliability performance of a given solution. Therefore, this paper proposed a framework to investigate the TCO, latency, and reliability performance of a set of fiber and microwave-based TN architectures. They were categorized based on their baseband functional split option and the reconfigurability capabilities of the equipment used. The results, based on real data from a non-incumbent operator, show that, in most of the considered scenarios, a microwave-based TN exhibits a lower TCO than a fiber-based one. The TCO gain may vary with the functional split option, geo-type, reconfigurability features, fiber trenching costs, and cost of microwave equipment, with a more significant impact in a dense urban geo-type, where for a low-layer functional split option, the fiber- and microwave-based architectures have a comparable TCO. Finally, it was found that the considered fiber and microwave architectures have almost similar average latency and connection availability performance. Both are suitable to meet the service requirements of 5G and beyond 5G services in most of the considered scenarios. Only in extreme latency-critical scenarios, a small number of the cells might not fully satisfy the latency requirements of a low-layer split option due to multiple microwave hops in the microwave-based architecture.

Marine vessel powertrain design optimization: Multiperiod modeling considering retrofits and alternative fuels

Over the coming decades, maritime transportation will transition from fossil hydrocarbon fuels to hydrogen, ammonia, and synthetic hydrocarbon fuels produced using renewable electricity as the primary energy source. In this context, a shipowner needs to identify a cost-efficient plan for the adoption of alternative fuels and onboard energy conversion system retrofits. This paper presents a multiperiod decision model for the selection of energy system components under increasingly stringent CO2 emissions regulations and cost forecasts over a multidecade planning horizon. The model considers the choice of newbuild architecture, timing of retrofits, component sizes, and allocation of fuels to converters with the objective of minimizing total cost of ownership (TCO). The decision problem is formulated as a discrete time multiperiod mixed-integer linear program. The application of the model is numerically illustrated for a Baltic Sea roll-on/roll-off ferry. The main findings are: (i) modifying the energy system with retrofits obtains 43% lower TCO compared to fuel switching alone; (ii) batteries contribute to 23% lower TCO; (iii) optimal component installation period can be shorter than their maximum lifetime; (iv) running an engine with hydrogen is favored over fuel cells and (v) hybrid propulsion is the key future-proofing design choice for short sea vessels.

Performance Evaluation of SiC-Based Two-Level VSIs with Generalized Carrier-Based PWM Strategies in Motor Drive Applications

Currently, silicon carbide (SiC) MOSFETs are several times higher in cost than the equivalent silicon (Si)-IGBTs; however, the gains in power conversion efficiency, simplification of thermal management, and energy savings in general bring the advantages of lower total cost of ownership. The implementation of discontinuous PWM (DPWM) techniques for controlling the motor drive brings further reductions for the semiconductor switching losses; however, most existing techniques have limited performance on the optimized clamping region, particularly at a low power factor, which is a common operation condition for motor drives employing the widely used V/f control, particularly at partial- or low-load conditions. This paper evaluates the performance of a SiC-based two-level voltage-source inverter (2L-VSI) motor drive operated with generalized carrier-based PWM methods. Theoretical analysis and experimental measurements are conducted in a 2.2 kW heatsink-less 2L-VSI prototype and induction machine, which demonstrates that the minimum switching losses DPWM (MSL-DPWM) is the most favorable solution in practice in terms of the achievable power conversion efficiency and harmonic distortions and also produces the least common-mode current, which is critical in motor drives.

Putting the foot down: Accelerating EV uptake in Kyrgyzstan

Road transport accounts for around 12% of global greenhouse gas (GHG) emissions. As many high-income countries are moving to decarbonise their road vehicle fleets, Kyrgyzstan – with rapid growth in passenger car ownership – is seeing a significant increase in transport-related GHG emissions and air pollution in urban areas. Whilst a transition to electric vehicles (EVs) is a key part of Kyrgyzstan’s Nationally Determined Contribution to the Paris Agreement, the potential for successful EV deployment in the region is under-researched. To fill this research gap, this paper presents an assessment of the potential for EV deployment in Kyrgyzstan. Firstly, we present an investigation of the policy and institutional landscape relating to transport and the promotion of EVs in Kyrgyzstan. Secondly, based on research of 50,000 car sales and interviews with 23 key stakeholders in the country, we present analysis of the existing Kyrgyz vehicle fleet. Thirdly, using information ascertained from the interviews and desk-based research, we conduct a Total Cost of Ownership assessment of EVs versus internal combustion engine vehicles (ICEVs) in the Kyrgyz context. We find that under the current conditions, EVs can have a lower total cost of ownership against similar ICEVs in Kyrgyzstan. However, it is evident that this is not typically the case: the analysis in this paper suggests that cost-competitiveness between EVs and ICEVs is more likely for larger and higher-powered vehicles, for which the ICEV version has a higher retail price. Finally, combining analysis of these results and analysis of the current conditions in Kyrgyzstan, trajectories for EV adoption in geographically and economically similar nations, and data from expert stakeholder interviews, we propose a set of policy recommendations to accelerate EV uptake in Kyrgyzstan.

Batteries, fuel cells, or engines? A probabilistic economic and environmental assessment of electricity and electrofuels for heavy goods vehicles

Uncertainty surrounding the total cost of ownership, system costs, and life cycle environmental impacts means that stakeholders may lack the required information to evaluate the risks of transitioning to low-carbon fuels and powertrains. This paper assesses the life cycle costs and well-to-wheel environmental impacts of using electricity and electrofuels in Heavy Good Vehicles (HGVs) whilst considering input parameter uncertainty. The complex relationship between electricity cost, electrolyser capacity factor, CO 2 capture cost and electricity emissions intensity is assessed within a Monte Carlo based framework to identify scenarios where use of electricity or electrofuels in heavy goods vehicles makes economic and environmental sense. For vehicles with a range of less than 450 km, battery electric vehicles achieve the lowest total cost of ownership for an electricity cost less than 100 €/MWh. For vehicles that require a range of up to 900 km, hydrogen fuel cell vehicles represent the lowest long-term cost of abatement. Power-to-methane and power-to-liquid scenarios become economically competitive when low-cost electricity is available at high-capacity factors and CO 2 capture costs for fuel synthesis are below 100 €/tCO 2 ; these fuels may be more applicable to decarbonise shipping and aviation. Battery electric HGVs reduce greenhouse gas emissions by 50% compared to the diesel baseline with electricity emissions of 350 gCO 2 e/kWh. Electricity emissions less than 35 gCO 2 e/kWh are required for the power-to-methane and power-to-liquid scenarios to meet EU emissions savings criteria. High vehicle capital costs and a lack of widespread refuelling infrastructure may hinder initial uptake of low-carbon fuels and powertrains for HGVs.

Vehicle‐to‐Grid Integration: Unlocking the Value of Scaled Electric Vehicle Adoption

Growth in electric vehicle (EV) adoption continues to accelerate and indicators suggest such growth will continue. Light‐duty EV sales in the United States rose by 66 percent in Q2 of 2022 over the same period in 2021, representing 5.3 percent of new sales in Q2 of 2022 vs. 2.7 percent in Q1 of 2021. EV sales in China and many European countries in 2021 represented more than a quarter of global new car sales. While the average upfront price of most light‐duty EVs is still higher than their gasoline equivalents, the fuel and maintenance savings often yield a lower total cost of ownership over a three‐to‐seven‐year period. Some analysts indicate that reaching 5 percent of sales is a key milestone in the transition to EVs, with many policy and market developments supporting this assertion.

Factors affecting cost competitiveness of electric vehicles against alternative powertrains: A total cost of ownership-based assessment in the Italian market

Electric vehicles have faced a significant diffusion in the last years, however they still represent a minority share over passenger cars registrations worldwide. Economic factors play a crucial role in preventing a higher diffusion of electric vehicles, with particular reference to the higher purchase price compared to internal combustion engine vehicles . Indeed, potential electric vehicles buyers typically tend to underestimate long-term savings that can be achieved due to the lower operating costs characterizing electric vehicles compared to internal combustion engine vehicles (so-called “energy-efficiency paradox”). An emerging literature stream suggests that the availability of comprehensive economic comparisons between electric vehicles and internal combustion engine vehicles, based on the total cost of ownership, would increase the potential customers’ willingness to buy an electric vehicle. However, there is an ongoing debate on the cost competitiveness of electric vehicles considering the whole ownership period, and in particular on the most influencing factors affecting it. The paper aims to fill this literature gap by assessing the cost competitiveness of electric vehicles against a broad set of alternative powertrains , with reference to the Italian market. To this aim, an ad hoc assessment tool based on the total cost of ownership has been developed, leveraging the extant knowledge on the topic and addressing current gaps. Results show that battery electric vehicles are characterized by the lowest total cost of ownership among analysed powertrains in two out of four vehicle segments evaluated, i.e., segments A (mini cars) and C (medium cars). This is mainly due to the presence of purchasing incentives and the lower fuel-related and non fuel-related operating costs characterizing battery electric vehicles compared to other powertrains, which more than offset the higher purchase price. In other cases, the relatively high purchase price characterizing battery electric vehicles (as well as plug-in hybrid electric vehicles) negatively affects their cost competitiveness. The study provides suggestions for managers of companies within the e-mobility value chain and policymakers on the levers to promote the spread of electric vehicles to achieve the decarbonisation targets for the transportation sector.

Comparative Analysis of Typical and Energy-Efficient Solutions of a Low-Rise Residential Building Based on a Bim Model

Energy efficient solutions reduce the amount of resources consumed, which leads to a lower total cost of ownership of real estate. The use of the BIM model makes it possible to evaluate the key indicators of energy-efficient solutions: heat transfer coefficient, specific annual values of energy consumption, fuel consumption, and carbon dioxide emissions into the atmosphere.Purpose of research. Develop and determine the feasibility of introducing energy efficient solutions based on the use of a BIM model of a low-rise building.Methods. The methodology is based on the study of the introduction of modern building technologies and standards in the Penza region, as well as the analysis of positive solutions to similar situations in the Russian Federation. To achieve the goal, the following tasks were solved: a BIM model was developed and the energy efficiency of a typical residential building was assessed; options for improving the energy efficiency of a typical low-rise residential building were identified; an energy report was drawn up for standard and energy-efficient buildings and the expediency of introducing energy-efficient solutions into a standard project was substantiated.Results. When developing energy-efficient solutions, it is advisable to use modern digital technologies. The BIM model of a typical low-rise residential building makes it possible to identify thermal blocks, zones within each of them, as well as structural elements of the building through which the main heat losses occur and develop options for improving the energy efficiency of the building. Based on the thermal blocks and zones allocated in the building, energy-efficient solutions have been developed, thanks to which heat losses through window openings and the front door are reduced from 3.04 to 0.63 W/m2K and from 2.11-0.79 W/m2K, respectively. Heat losses due to changes in the design of enclosing structures: walls and floors above the first floor decreased from 0.28 to 0.25 W/m2K and from 0.18 to 0.15 W/m2K, respectively.Conclusions.The BIM model of a building makes it possible to effectively conduct a comparative analysis of standard and energy-efficient solutions for low-rise buildings, taking into account the features of the planning solution and regional climatic features.

Configuration of Electric Vehicles for Specific Applications from a Holistic Perspective

Electrification of heavy-duty vehicles (HDVs) used for passengers and goods transportation is a key strategy to reduce the high levels of air pollution in large urban centers. However, the high investment cost of the commercially available electrified HDVs has limited their adoption. We hypothesized that there are applications where the operation with tailored electrified HDVs results in a lower total cost of ownership and lower well-to-wheel emissions of air pollutants, with higher acceleration capacity and energy efficiency than the fossil-fueled counterparts. The road transportation services running on fixed routes with short span distances (<50 km), such as the last mile cargo distribution and the passenger shuttle services, is a clear example with a high possibility of cost reduction through tailored electric HDVs. In this work, we present a methodology to define the most appropriate configuration of the powertrain of an electric vehicle for any given application. As a case study, this work aimed to define an electric powertrain configuration tailored for a university shuttle service application. A multi-objective weighted-sum optimization was performed to define the best geometrical gearbox ratios, energy management strategy, size of the motor, and batteries required. Based on three different driving profiles and five battery technologies, the results showed that, based on a 50 km autonomy, the obtained powertrain configuration satisfies the current vehicle operation with a reduced cost in every driving profile and battery technology compared. Furthermore, by using lithium-based batteries, the vehicle’s acceleration capacity is improved by 33% while reducing energy consumption by 37%, CO2 emissions by 31%, and the total cost of ownership by 29% when compared to the current diesel-fueled buses.

Impact of fuel cell range extender powertrain design on greenhouse gases and NOX emissions in automotive applications

Fuel cell (FC) technologies for mobility are gaining interest as promising options to decarbonize the transport sector in line with the current progress towards the H2 economy. Previous studies show how the fuel cell range extender (FCREx) powertrain architecture can offer flexible and efficient operation along with the potentially low total cost of ownership (TCO) in passenger car applications. Cradle-to-grave emissions of these vehicles have not been estimated, nor their variation with the components sizing or the H2 production pathway analyzed. In this study, the life cycle assessment (LCA) and sizing methodologies were combined to address these knowledge gaps. The design spaces were generated by varying the FC maximum power, the battery capacity and the H2 tank capacity and by simulating the resulting designs with the WLTC 3b driving cycle. Then, the lifetime H2 and energy consumption results and design parameters were calculated and used as inputs to estimate the greenhouse gases (GHG) and NOX emissions on the manufacturing and fuel production cycles. From the results, it was proven how considering steam methane reforming (SMR) with carbon capture and storage (CCS) as the H2 production pathway could decrease by 60% and 38% GHG-100 and NOX emissions respectively, with respect to electrolysis where electricity is generated with the EU mix. The optimum design, in terms of emissions, was found to be with low-moderate battery capacity and moderate-high FC maximum power in contrast to the optimum design for performance, which had high battery capacity and high FC stack power.

Comparative TCO Analysis of Battery Electric and Hydrogen Fuel Cell Buses for Public Transport System in Small to Midsize Cities

This paper shows the results of an in-depth techno-economic analysis of the public transport sector in a small to midsize city and its surrounding area. Public battery-electric and hydrogen fuel cell buses are comparatively evaluated by means of a total cost of ownership (TCO) model building on historical data and a projection of market prices. Additionally, a structural analysis of the public transport system of a specific city is performed, assessing best fitting bus lines for the use of electric or hydrogen busses, which is supported by a brief acceptance evaluation of the local citizens. The TCO results for electric buses show a strong cost decrease until the year 2030, reaching 23.5% lower TCOs compared to the conventional diesel bus. The optimal electric bus charging system will be the opportunity (pantograph) charging infrastructure. However, the opportunity charging method is applicable under the assumption that several buses share the same station and there is a “hotspot” where as many as possible bus lines converge. In the case of electric buses for the year 2020, the parameter which influenced the most on the TCO was the battery cost, opposite to the year 2030 in where the bus body cost and fuel cost parameters are the ones that dominate the TCO, due to the learning rate of the batteries. For H2 buses, finding a hotspot is not crucial because they have a similar range to the diesel ones as well as a similar refueling time. H2 buses until 2030 still have 15.4% higher TCO than the diesel bus system. Considering the benefits of a hypothetical scaling-up effect of hydrogen infrastructures in the region, the hydrogen cost could drop to 5 €/kg. In this case, the overall TCO of the hydrogen solution would drop to a slightly lower TCO than the diesel solution in 2030. Therefore, hydrogen buses can be competitive in small to midsize cities, even with limited routes. For hydrogen buses, the bus body and fuel cost make up a large part of the TCO. Reducing the fuel cost will be an important aspect to reduce the total TCO of the hydrogen bus.

Detailed modeling of solids separation by microsieving in a rotating belt filter: Explicit effect of particle size, mesh size, and polymer dose

Microsieving by rotating belt filters is an engineered fractionation method for particle separation from wastewater that can be used as an alternative to primary clarification due to its smaller footprint and lower total cost of ownership. Because of the multiscale nature of the filtration processes involved, and the interdependent variables controlling performance and the system design, the availability of verified and comprehensively validated models that, based on fundamental principles, can explicitly capture the effect of particle size, mesh size and polymer dose are essential for performance optimization and scale-up. In this paper, a detailed microsieving filtration model was derived by extending Darcy’s law to a dual-layer dynamic framework whose predictions were validated against batch (column) and continuous flow (RBF pilot) experimental data. The ability of the microsieving model to accurately capture observed trends confirmed that the model formulation, derived from column experiments, were sufficiently accurate and flexible to capture the relevant physics involved, with a relative error in performance scale up (from column to pilot) of 33% and 14% for filter capacity and effluent total suspended solids, respectively. Upon further calibration against pilot data, the relative error was reduced to 9% and 5%, respectively, indicating the suitability of the model structure in further adapting to filtration process conditions occurring at pilot scale. Finally, the calibrated model was used to derive guidance for future pilot studies. It was determined that, under naturally varying influent conditions, at least 8 h of continuous pilot data, with sampling frequency of at least 15 min for filter capacity and suspended solids concentration, were necessary for a satisfactory estimate of the model parameters.

How Policies Affect the Dissemination of Electric Passenger Cars Worldwide

Road transportation is one of the largest emitters of greenhouse gas emissions. The EU set the target to reduce overall transport emissions by 60% by 2050 compared to 1990. Electric mobility is considered a proper means to achieve this goal. Battery electric vehicles (BEVs) are a mature technology. The high investment costs, limited driving range and a charging infrastructure that is not extensive yet are currently the main challenges. This work analyses how policies affect the dissemination of BEVs in selected countries with remarkable market shares of BEVs. The core objective is to investigate how policies affect BEV economics compared to conventional car economics. Financial policies and their effects on BEVs for the major markets of China, the USA and Europe were analysed. To do so, the total cost of ownership (TCO) was calculated for each country. The major conclusions were: (i) The investment cost of a car had the most significant impact on the TCO; (ii) Low TCO as an incentive was not enough to ensure successful BEV dissemination; (iii) Non-monetary incentives such as access to certain zones and the usage of bus lanes for BEVs combined with registration taxes, low electricity prices and high fuel prices were very favourable conditions.

Improving the cost efficiency of large-scale cloud systems running hybrid workloads - A case study of Alibaba cluster traces

The pandemic of coronavirus has dramatically disrupted the retail industry, as many stores are forced to close and people across the world are shelter-in-place with online shopping as the inevitable choice. To meet the rapidly increasing demand for e-commerce, more data centers are expected to provide new or significantly improve existing cloud services that can better support hybrid workloads (e.g. online purchase jobs and batch jobs that support ranking or recommendation systems). Successful cloud systems need to efficiently handle and quickly respond to huge volume of traffic with such hybrid workloads. Meanwhile, it is critical to reduce the total cost of ownership (TCO) for profitability. Improving system utilization is one of the effective techniques to achieve the twin goals of high performance and low TCO. This paper conducts a comprehensive analysis on the 2017 and 2018 cluster traces released by Alibaba, which provides a case study about Alibaba's best practices in improving the performance and cost efficiency of its large-scale cloud systems by consolidating time-sensitive online service jobs with time-insensitive batch jobs. Our investigation indicates that the over-subscription (causing resource waste and low utilization) and under-subscription (causing performance degradation) problems co-exist in the current Alibaba system. We develop a simulator that allows us to evaluate possible solutions to address this problem and their impact on the performance, energy consumption, and TCO. Our experiments show that the estimated TCO can be reduced by $600,000 for the 2018 trace running on over 4,000 machines without compromising performance. The TCO can decrease by nearly $68 million if similar strategy is extrapolated to Alibaba's 432,000 web facing servers.

Pricing and free periodic maintenance service decisions for an electric-and-fuel automotive supply chain using the total cost of ownership

Although subsidies have had significant impacts on the electric vehicle (EV) market share, many governments have planned to eliminate subsidies. There is a concern that unsubsidized EVs reduce the EV market share, significantly. However, purchasing an EV instead of a fuel vehicle (FV) might impose a lower total cost of ownership (TCO) on customers, depending on their vehicle usage. In this case, supply chains could optimize their decisions considering which vehicle is affordable for each customer class from the view of TCO. This study investigates optimal pricing and free periodic maintenance service (FPMS) decisions in a two-stage electric-and-fuel automotive supply chain, considering TCO to estimate vehicle market shares under customer classification with different vehicle usage patterns. Two bi-level models are developed and solved through Karush-Kuhn-Tucker equations and a reformulation-and-decomposition algorithm. Sensitivity analyses are performed considering various scenarios on energy prices and ownership periods. Results indicate that the high-usage customers are more likely to purchase an EV if the ownership period is the same for all classes. However, if low-usage customers keep the vehicle for a longer period than the others, they are more likely to purchase an EV. Both providing FPMSs by the manufacturer instead of the retailer and increasing the fuel price over time with a higher rate, compared with the electricity price and the inflation rate, improve the EV market share and reduce the total fuel consumption and emissions. Investment to produce EVs is not economical for a high price of electricity while having low fuel prices.

The Application of Total Cost of Ownership Method to Automotive Industry

Abstract Transport currently has the largest share of air pollution, among all sectors. Increasing air pollution caused by conventional cars brings an opportunity to develop electric cars, which are a green alternative in transport. The main aim of the article was to explain the terms related to electromobility through the literature and then to examine the total cost of electric cars and conventional cars on the example of selected four models. The comparison was made on the example of the best-selling four selected models: electric car, hybrid car, plug-in hybrid car and standard petrol car. The methods were used in the elaboration of the article: analysis, synthesis, induction, deduction and comparison. We used the Total Cost of Ownership (TCO) method to process the results. The intention of the article was to point out the lower total cost of ownership for electric cars and to confirm the fact that electric cars are a profitable investment in the future.

Range cost-effectiveness of plug-in electric vehicle for heterogeneous consumers: An expanded total ownership cost approach

Plug-in electric vehicles (PEV) appears to have sales momentum in major personal vehicle markets but are still at the early market stage. Opportunities to accelerate PEV adoption can be discovered through comprehensive total cost of ownership (TCO) analysis. Understanding the cost-effective electric ranges of PEVs for consumers, manufacturers, and the society is critical for any discussion of PEV mass markets. This study expanded the traditional TCO approach by (1) fully considering heterogeneous consumer driving patterns, (2) quantifying the charging inconvenience and range anxiety cost of battery-electric vehicles (BEVs), and (3) monetizing both tangible and intangible PEV policies. Uncertainties were handled through Monte Carlo simulation. The results suggest that BEVs with an electric range of 250–350 km have the lowest TCO in cities with government-enacted purchase limitations, and internal combustion engine vehicles (ICEVs) have the lowest TCO in cities without purchase limitations, even when considering PEV subsidies. The lowest TCO for some consumer groups is obtained by BEVs with an electric range of 400–450 km, especially in northern China, where the weather is colder. The cost-effective all-electric range for BEVs in each city in 2025 will decrease due to improved battery performance in cold environments and an expanded charging infrastructure. Based on TCO, plug-in hybrid electric vehicles (PHEVs) are currently more suitable for drivers with a high average daily mileage or a large mileage variance. However, by 2025, BEVs with a long driving range may become a more cost-effective choice for these drivers.