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"vehicle performance"
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Design of a Hybrid Electric Vehicle Powertrain for Performance Optimization Considering Various Powertrain Components and Configurations
Emissions from the transportation sector due to the consumption of fossil fuels by conventional vehicles have been a major cause of climate change. Hybrid electric vehicles (HEVs) are a cleaner solution to reduce the emissions caused by transportation, and well-designed HEVs can also outperform conventional vehicles. This study examines various powertrain configurations and components to design a hybrid powertrain that can satisfy the performance criteria given by the EcoCAR Mobility Challenge competition. These criteria include acceleration, braking, driving range, fuel economy, and emissions. A total of five different designs were investigated using MATLAB/Simulink simulations to obtain the necessary performance metrics. Only one powertrain design was found to satisfy all the performance targets. This design is a P4 hybrid powertrain consisting of a 2.5 L engine from General Motors, a 150 kW electric motor with an electronic drive unit (EDU) from American Axle Manufacturing, and a 133 kW battery pack from Hybrid Design Services.
Journal Article
Factors influencing adoption of electric vehicles - A case in India
The ever-growing environmental concerns caused due to fossil fuel depletion and greenhouse gas (GHG) emissions has paved way for consumers to consider Electric Vehicles (EV) as a rapidly emerging operational alternative to vehicles that run on fossil fuels like petrol, diesel and CNG. The paper aims to identify the possible factors in consumers' intention of Electric Vehicle adoption. A quantitative approach is adopted and the data is collected from 172 respondents from Bengaluru through an online survey method using snowball sampling method. A robust statistical method, such as exploratory factor analysis is conducted using IBM SPSS 23 to identify the factors. The study identified factors such as Financial Barriers, Vehicle Performance Barriers, Lack of charging infrastructure, Environmental Conservation, Societal Influence, Social Awareness of Electric Vehicles as influencers towards electric vehicle adoption. The outcome of the study helps the policymakers to modify the current policy with respect to electric vehicle in the emerging nations.
Journal Article
Predicting the Future Manufacturing Cost of Batteries for Plug-In Vehicles for the U.S. Environmental Protection Agency (EPA) 2017–2025 Light-Duty Greenhouse Gas Standards
In developing the U.S. 2017–2025 Light-Duty Vehicle Greenhouse Gas Emissions Standards, the U.S. Environmental Protection Agency (EPA) modeled lithium-ion battery packs for future electrified vehicles to estimate their direct manufacturing costs through 2025. As part of the 2016 Midterm Evaluation of the standards for model years (MY) 2022 to 2025, the analysis was revised to account for developments in battery design since the 2012 rulemaking. This paper describes the methodology that was used for estimating battery capacity, power, and cost, and compares the projected cost estimates to other sources. An empirical equation is derived for specifying motor power as a function of target acceleration time, and suggested factors for converting cell-level costs to pack-level costs are developed.
Journal Article
An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows
The pickup and delivery problem with time windows is the problem of serving a number of transportation requests using a limited amount of vehicles. Each request involves moving a number of goods from a pickup location to a delivery location. Our task is to construct routes that visit all locations such that corresponding pickups and deliveries are placed on the same route, and such that a pickup is performed before the corresponding delivery. The routes must also satisfy time window and capacity constraints.
This paper presents a heuristic for the problem based on an extension of the large neighborhood search heuristic previously suggested for solving the vehicle routing problem with time windows. The proposed heuristic is composed of a number of competing subheuristics that are used with a frequency corresponding to their historic performance. This general framework is denoted adaptive large neighborhood search .
The heuristic is tested on more than 350 benchmark instances with up to 500 requests. It is able to improve the best known solutions from the literature for more than 50% of the problems.
The computational experiments indicate that it is advantageous to use several competing subheuristics instead of just one. We believe that the proposed heuristic is very robust and is able to adapt to various instance characteristics.
Journal Article
Gear Ratio Optimization along with a Novel Gearshift Scheduling Strategy for a Two-Speed Transmission System in Electric Vehicle
A novel gearshift scheduling strategy has been framed for a two-speed transmission system in electric vehicles that can save energy during hilly driving and frequently changing driving conditions through efficient electric motor operation. Unlike the traditional approach, the proposed gearshift strategy is based on the preferred vehicle speed range, vehicle acceleration, and road grade to ensure desired vehicle performances with minimum energy consumption. Meanwhile, the vehicle speed range is chosen around the electric motor rated speed, and two gearshift schedules in relation to vehicle acceleration and road grade are developed based on the motor torque generating capacity and efficiency. Appropriate gear is selected through a combined assessment of the required vehicle speed, acceleration, and road grade information. A guideline is developed and explained for the primary gearshift schedule. Next, the gear ratios and gearshift schedules are optimized combinedly in a Simulink environment using the gradient descent method and pattern search method on three driving cycles separately. Depending on the driving scenarios, around 4% to 7.5% energy saving has been experienced through optimization, while the gear ratios and gearshift schedule in relation to the road grade are found to be major contributors to the vehicle economic driving compared to that with the gearshift schedule for vehicle acceleration.
Journal Article
Performance and Efficiency Trade-Offs in Brazilian Passenger Vehicle Fleet
The rate of technological progress is an important metric used for predicting the energy consumption and greenhouse gas emissions of future light-duty fleets. A trade-off between efficiency and performance is essential due to its implications on fuel consumption and efficiency improvement. These values are not directly available in the Brazilian fleet. Hence, this is the main gap in knowledge that has to be overcome. Tendencies in all relevant parameters were also unknown, and we have traced them as well, established on several publications data and models. We estimate the three indicators mentioned above for the Brazilian fleet from 1990 to 2020. Although the rate of technological progress was lower in Brazil than that in developed countries, it has increased from 0.39% to 0.61% to 1.7% to 1.9% in subsequent decades. Performance improvements offset approximately 31% to 39% of these efficiency gains. Moreover, the vehicle market is shifting toward larger vehicles, thus offsetting some efficiency improvements. We predict the fleet fuel efficiency for the years 2030 and 2035 using the above-mentioned factors. The predicted values for efficiency can vary by a factor of two. Thus, trade-off policies play a vital role in steering toward the desired goals of reducing the transportation sector’s impact on the environment.
Journal Article
The Impact of Variable Ambient Temperatures on the Energy Efficiency and Performance of Electric Vehicles during Waste Collection
The market for electric cars (EVs) is growing quickly, which has led to a diversity of models and significant technological advancements, particularly in the areas of energy management, charging, range, and batteries. A thorough analysis of the scientific literature was conducted to determine the operational and technical parameters of EVs’ performance and energy efficiency, as well as the factors that influence them. This article addresses the knowledge gap on the analysis of ambient temperature-related parameters’ effects on electric garbage trucks operating in particular urban traffic conditions for selective waste collection. To optimize vehicle routes, a computational model based on the Vehicle Routing Problem was used, including the Ant Colony Optimization algorithm, considering not only the load capacity of garbage trucks but also their driving range, depending on the ambient temperature. The results show that the median value of collected bulky waste for electric waste collection vans, depending on the ambient temperature, per route is 7.1 kg/km and 220 kg/h. At a temperature of −10 °C, the number of points served by EVs is 40–64% of the number of points served by conventional vehicles. Waste collection using EVs can be carried out over short distances of up to 150 km, which constitutes 95% of the optimized routes in the analyzed case study. The research contributed to the optimal and energy-efficient use of EVs in variable temperature conditions.
Journal Article
Effects of Gasoline and LPG on the Performance and Emissions of a Turbocharged Direct-Injection Vehicle: A Response Surface Methodology Approach
This study aims to investigate the performance and emission characteristics of advanced liquid-phase Liquefied Petroleum Gas (LPG) injection systems retrofitted to gasoline engines. In experiments, a four-stroke, four-cylinder, direct-injection system turbocharged gasoline vehicle was driven on a dynamometer, and wheel power values were measured at different gear intervals and speeds. Additionally, Carbon monoxide (CO), Carbon dioxide (CO2), Hydrocarbons (HC), Oxygen (O2), and lambda values were measured using an exhaust emission device. In this study, the results obtained from vehicle tests using LPG and gasoline fuels were investigated by response surface methodology. The input factors for the Response Surface Methodology were determined to be speed and gear spacing, and the response values were determined to be wheel power, CO, CO2, HC, O2, and lambda values. As a result, when examining the power values, it is observed that during operation in LPG mode, the 2nd, 3rd, 4th, and 5th gears exhibit increases of approximately 2.94%, 2.38%, 1.85%, and 13%, respectively, compared to operation in gasoline mode. Conversely, during operation in gasoline mode, the 6th and 7th gears show increases of approximately 1.03% and 1.07%, respectively, compared to operation on LPG. When the exhaust emission values are examined, it is determined that the vehicle emits more ideal emissions when operating in LPG mode compared to gasoline mode and meets the standards. Future work should investigate the thermodynamic and combustion characteristics of liquid LPG under varying engine loads and ambient conditions. Advanced modeling techniques, such as machine learning-assisted optimization and real-time control algorithms, could enhance fuel efficiency and emission control. Additionally, system integration studies and component-level durability analyses will be essential for commercialization.
Journal Article
The Lure of the Virtual
Although organizational scholars have begun to study virtual work, they have yet to fully grapple with its diversity. We draw on semiotics to distinguish among three types of virtual work (virtual teams, remote control, and simulations) based on what it is that a technology makes virtual and whether work is done
with or
on
,
through
, or
within
representations. Of the three types, simulations have been least studied, yet they have the greatest potential to change work's historically tight coupling to physical objects. Through a case study of an automobile manufacturer, we show how digital simulation technologies prompted a shift from symbolic to iconic representation of vehicle performance. The increasing verisimilitude of iconic simulation models altered workers' dependence on each other and on physical objects, leading management to confound operating
within
representations with operating
with or
on
representations. With this mistaken understanding, and lured by the virtual, managers organized simulation work in virtual teams, thereby distancing workers from the physical referents of their models and making it difficult to empirically validate models. From this case study, we draw implications for the study of virtual work by examining how changes to work organization vary by type of virtual work.
Journal Article