Browse Topic: Drive cycles

Items (844)
This paper proposes a theoretical drive cycle for the competition, considering the battery pack project under design. The vehicle has a non-reversible, double-stage gear train, created without a dynamic investigation. To evaluate the effect on performance, several ratios were analyzed. Dynamic model uses Eksergian’s Equation of Motion to evaluate car equivalent mass (generalized inertia), and external forces acting on the vehicle. The circuit is divided into key locations where the driver is likely to accelerate or brake, based on a predicted behavior. MATLAB ODE Solver executed the numerical integration, evaluating time forward coordinates, creating the drive cycle. Linear gear train results provided data as boundary conditions for a second round of simulations performed with epicyclic gear trains. Model is updated to include their nonlinearity by differential algebraic equation employment with Lagrange multipliers. All data undergoes evaluation to ascertain the mechanical and
Rodrigues, Patrícia Mainardi TortorelliSilveira, Henrique Leandro
The transition from Internal Combustion Engine (ICE) Vehicles to Electric Vehicles (EVs) has catalyzed significant advancements in battery technology, prioritizing safer and more reliable energy storage solutions. Although Lithium Iron Phosphate (LFP) batteries are recognized for their safety, they rely on critical and market-volatile elements such as copper, lithium, and graphite. To address these challenges, sodium-ion batteries (SIBs) have emerged as sustainable alternatives that are particularly suited for low-speed EVs. Ensuring the seamless integration of SIBs into EV battery packs necessitates preparedness for the rapid evolution of SIB technology. Model-based approaches, including Equivalent Circuit Models (ECMs), are crucial for developing advanced Battery Management Systems (BMSs) and State of Charge (SoC) estimation algorithms that enable precise battery control. This study comprehensively evaluates various order Resistance-Capacitance (RC) ECM configurations to accurately
Ns, Farhan Ahamed HameedGupta, ShubhamJha, Kaushal
In recent years, Lithium Iron Phosphate (LFP) has become a popular choice for Li-ion battery (LIB) chemistry in Electric Vehicles (EVs) and energy storage systems (ESS) due to its safety, long lifecycle, absence of cobalt and nickel, and reliance on common raw materials, which mitigates supply chain challenges. State-of-charge (SoC) is a crucial parameter for optimal and safe battery operation. With advancements in battery technology, there is an increasing need to develop and refine existing estimation techniques for accurately determining critical battery parameters like SoC. LFP batteries' flat voltage characteristics over a wide SoC range challenge traditional SoC estimation algorithms, leading to less accurate estimations. To address these challenges, this study proposes EKF and PF-based SoC estimation algorithms for LFP batteries. A second-order RC Equivalent Circuit Model (ECM) was used as the dynamic battery model, with model parameters varying as a function of SoC and
Ns, Farhan Ahamed HameedJha, KaushalShankar Ram, C S
ABSTRACT The paper presents the fuel economy and performance capabilities of a switchable P2/P3 Hybrid Transmission for commercial and military use cases through modeling and simulation. An overview of the simulation model developed to analyze the vehicle performance and fuel consumption for a specified drive cycle is presented. The model includes the key components of the electrified powertrain including engine, hybrid transmission, electric motor and battery. Use cases were identified to represent Commercial vocational applications and military analogues. The results of P2/P3 Hybrid Powertrain model simulation are compared with that obtained from a model of baseline Conventional Torque Converter Automatic Transmission (AT). The comparison is made for both vehicle performance and fuel economy, and the results indicate that the P2/P3 Hybrid Transmission demonstrates better fuel economy with same or better performance than the baseline heavy-duty automatic transmission. Opportunities to
Patil, ChinmayaThanom, WittDykes, ErikKreucher, JoshGenise, Thomas
ABSTRACT Fuel economy improvements were investigated for the FMTV platform considering alternative transmissions and final drive ratio. An FMTV-M1078 with Caterpillar C7 engine and Allison 3700SP transmission was the target vehicle of this study. Experimental data were collected while vehicle was operated over the FTP72 test cycle. Base vehicle data (vehicle weight, coast-down times, etc.) were collected to provide comparison data for establishing the baseline analytical vehicle model. Experimental data were processed to determine road load parameters, engine BSFC map, transmission shift schedule and similar for populating the analytical model. Modeling was performed using GT-Drive. The model was analyzed over the same defined drive cycle used to collect the experimental data. Once the model was correlated to the experimental data, updates were made for the variants in transmission and drive-line parameters to be used in the fuel economy study. The difference between experimental
Van Benschoten, MattNelson, Evan
ABSTRACT The U.S. Department of Defense faces growing fuel demand, resulting in increasing costs and compromised operational capability. In response to this issue, the Fuel Efficient Ground Vehicle Demonstrator (FED) program was initiated in order to demonstrate a tactical vehicle with significantly greater fuel efficiency than a Humvee while maintaining capability. This article provides an overview of a systems engineering methodology for maximizing fuel efficiency and its application in concept development for the FED program. Engineering tools and methods used include tradespace definition, provisional baseline product models, decomposition of energy expenditure over the product usage cycle, structured technology market surveys, complex systems modeling & simulation tools, and design space exploration / Pareto optimization. The methodology explores the impact of technology on fuel efficiency along with other aspects of vehicle development including drive cycle definition
Luskin, PaulBerlin, Robert
ABSTRACT The US Army Ground Vehicle Programs use various drive cycles for testing and validation of new vehicle systems and models. These cycles have traditionally been characterized by run speed, number of stops, and terrain profile. For the sake of powertrain analysis, there have been a number of additional metrics proposed for characterization of such drive cycles in the context of fuel economy evaluation. This paper examines several metrics related to fuel economy, comparing standard Army test circuits, simulated drive cycles, and commercially standardized drive cycles. By comparing these cycles and identifying key metrics, we can develop better testing plans and bench cycles for technology evaluation. Field data from a mountainous region shows substantial variability that is not fully captured by current test cycles. Kinetic intensity is able to differentiate between the human in the loop scenarios, with values higher in simulated cycles than in field data. However, number of
Sebeck, KatherineMange, JeremyMacLennan, JamieRizzo, Denise
ABSTRACT The recent climate change plan for the United States Army states that hybridized combat vehicles will enter the fleet by 2050. The Bradley Fighting Vehicle (BFV) and its family of vehicles are prime candidates for hybridization. This paper sets out to perform a drive cycle analysis for the BFV using its traditional powertrain along with hybridized powertrains. The analysis considers both series and parallel hybrid architectures, where the size of the batteries are based on modifications to the existing powertrain. Three different drive cycles are considered – stationary, highway, and off-road. The model accounts for accelerative forces, transmission losses, cooling losses, drag, road grade, tractive losses, and ancillary equipment. The results indicate that both parallel and series hybrids provide reduced fuel consumption and increased range. Of the two, the series hybrid architecture provides more overall benefits. The study concludes by discussion of the technical challenges
Razon, CourtneyMittal, Vikram
ABSTRACT This paper discusses the development of a methodology to generate drive cycles having a finite duration, but which are statistically representative of a larger set of usage data collected from fleet vehicles operating in the field. Given field-generated time vs. velocity data, acceleration at each data point is calculated, and each velocity and acceleration pair is binned using some calibrated level of fidelity. As a result, a velocity-acceleration matrix representing each vehicle operating point, as well as cumulative probability distribution functions for acceleration change and take-off acceleration are generated. These cumulative distribution functions are utilized to pick random velocity-acceleration pairs from the corresponding matrix, and the concatenation of each consecutive chosen velocity-acceleration pair constitutes the final drive cycle. Three drive cycles representing the high-, medium- and low-speed operation of the vehicle are generated from the field data, and
Dagci, Oguz H.Cook, AndrewShaw, Phillip
Abstract This paper presents the development of a transmission-in-the-loop (TiL) experimentation system. In this TiL experimental setup, the input side of the transmission is controlled by a dynamometer emulating the engine, while the output sides of the transmission are controlled by two dynamometers emulating the wheels and vehicle. The models emulating these vehicle components are required to possess sufficient fidelity to simulate engine torque pulse (ETP) and wheel slip dynamics while being computationally efficient to run in real-time. While complex engine and tire models exist in the literature that accurately capture these dynamics, they are often too numerically stiff for real-time simulation. This paper presents the system level details of such a TiL setup, and the modeling concepts for the development of high fidelity real-time models of the engine and tire dynamics for use in this experiment. Parameters of the engine model are identified using experimental data. Vehicle
Nutter, Don
Vehicle electrification has gained prominence in various industries and offers sustainability opportunities, especially in the context of heavy-duty vehicles such as school buses. Despite the prevalence of conventional diesel school buses (CDSB), the adoption of electric school bus (ESB) and other eco-friendly alternatives is increasing. In the United States alone, there has been a notable increase in the adoption of ESBs, indicating substantial growth. The electrification of school buses not only promises energy savings, but also offers health benefits to children, reduced greenhouse gas emissions, and environmentally friendly transportation practices, aligned with broader eco-friendly initiatives. This paper investigates the potential for energy savings and reduction in environmental footprint through electrification of school buses in the Columbus, OH area. Analyzing current bus routes and road terrain data allows one to estimate energy demand and environmental impact, accounting
Moon, JoonHanif, AtharAhmed, Qadeer
The automotive industry faces significant obstacles in its efforts to improve fuel economy and reduce carbon dioxide emissions. Current conventional automotive powertrain systems are approaching their technical limits and will not be able to meet future carbon dioxide emission targets as defined by the tank-to-wheel benchmark test. As automakers transition to low-carbon transportation solutions through electrification, there are significant challenges in managing energy and improving overall vehicle efficiency, particularly in real-world driving scenarios. While electrification offers a promising path to low-carbon transportation, it also presents significant challenges in terms of energy management and vehicle efficiency, particularly in real-world scenarios. Battery electric vehicles have a favorable tank-to-wheel balance but are constrained by limited range due to the low battery energy density inherent in their technology. This limitation has led to the development of hybrid
Kraljevic, IvicaSpicher, Ulrich
For a three-wheeler, this research studies the aging effects on an LFP battery across a realistic three-wheeler commercial vehicle cycle simulated in GT-SUITE. The study evaluates how thermal management affects battery aging with different battery cooling methods and triggering temperatures for cooling activation. The three-wheeler analysis cycle includes a real-world drive cycle, followed by battery recharging, and then a rest period. This sequence repeats until the battery ages to 80% of its original capacity (end of life). Battery life is determined using various methods of battery cooling and the temperatures that trigger the activation of cooling mechanisms. Different heat transfer coefficients (HTCs) are derived or assumed based on the cooling method used
Chandna, AshishChopra, Ujjwal
Nowadays, Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are becoming popular globally due to increasing pollution levels in the environment and expensive conventional non-renewable fuels. Li-ion battery EV’s have gained attention because of their higher specific energy density, better power density and thermal stability as compared to other cell chemistries. Performance of the Li-ion battery is affected by temperatures of the cells. For Li-ion cells, optimum operating temperature range should be between 15-35 °C [1]. Initially, small battery packs which are cooled by air were used but nowadays, large battery packs with high power output capacities being used in EV’s for higher vehicle performance. Air based cooling system is not sufficient for such batteries, hence, liquid coolant based cooling systems are being introduced in EV’s. Computational Fluid Dynamics (CFD) simulation can be used to get better insight of cell temperature inside battery. But it is complex, time
Kumar, VivekSHENDRE, Mohit
In an electric vehicle, nevertheless, the primary component is the electric motor (e-motor). Understanding the thermal performance of the e-motor is paramount in ensuring the overall efficient functioning of the electric vehicle. Usually, the high-power e-motors are oil-cooled due to relatively high thermal loads. The e-motor thermal response is monitored under extreme conditions like warm-up cycle allowing the vehicle to move in a circular track multiple-times. In this condition, the vehicle undergoes heavy lateral and longitudinal accelerations, the e-motor speed varies and the consequent thermal losses from the rotor and stator components also vary accordingly. Importantly, the cooling oil sloshes rigorously that affects the heat removal capacity of the oil. The advanced capabilities of Computational Fluid Dynamics (CFD) allow to virtually simulate the warm-up cycle and capture the extremely transient thermal response of the e-motor in the given conditions. In the current effort, a
Pasunurthi, Shyam SundarSrinivasan, ChiranthChaudhari, NiravMaiti, Dipak
Light commercial vehicles are an indispensable element for the transport of people and the delivery of goods, especially on extra-urban and long-distance routes. With a view to sustainable mobility, it is necessary to think about hybridizing these vehicles to reduce the fuel consumption as well as greenhouse gas emissions and particulate matter. These types of vehicles are generally powered by diesel and travel many kilometers a day. On the other hand, the use of light commercial vehicles in battery electric vehicle (BEV) configuration has already been started but is not receiving widespread recognition. In this panorama, starting from a study already developed for the hybridization of a plug-in light commercial vehicle in Worldwide harmonized Light vehicles Test Cycle (WLTC) condition, the simulation analysis has been extended to the plug-in hybrid vehicle (PHEV) operating in real driving emission conditions (RDE). In particular, using Advisor software, a vehicle has been simulated in
Mancaruso, EzioMeccariello, GiovanniRossetti, Salvatore
Electrification or hybridization of commercial vehicles offers a promising avenue for mitigating emissions in urban environments. This concept is particularly applicable to waste collection vehicles, which move in urban contexts along repeatedly chosen driving cycles. Municipal waste collection and transport are functional tasks which have a significant impact on the urban environment in terms of energy consumption and CO2 emissions. In this work, the evaluation of a full-electric powertrain was carried out for a small size waste collection vehicle operating in the historic center of the city of Perugia (Italy). First, the vehicle model was developed and validated against literature data using a full-electric powertrain. The model allows to evaluate energy consumption and system efficiency considering the real driving path and the mass variation due to the waste collected during the route. Real driving data (position, slope, collection stops) were obtained through an experimental
Zembi, JacopoBistoni, LorenzoCinti, GiovanniCastellani, BeatriceBattistoni, Michele
The need to reduce vehicle-related emissions in the great cities has led to a progressive electrification of urban mobility. For this reason, during the last decades, the powertrain adopted for urban buses has been gradually converted from conventional Internal Combustion Engine (ICE), diesel, or Compressed Natural Gas (CNG), to hybrid or pure electric. However, the complete electrification of Heavy-Duty Vehicles (HDVs) in the next years looks to be still challenging therefore, a more viable solution to decarbonize urban transport is the hybrid powertrain. In this context, the paper aims to assess, through numerical simulations, the benefits of a series hybrid-electric powertrain designed for an urban bus, in terms of energy consumption, and pollutants emissions. Particularly a Diesel engine, fueled with pure hydrogen, is considered as a range extender. The work is specifically focused on the design of the Energy Management Strategy (EMS) of the series-hybrid powertrain, by comparing
Nacci, GianlucaCervone, DavideFrasci, EmmanueleLAKSHMANAN, Vinith KumarSciarretta, AntonioArsie, Ivan
Growing environmental concerns drive the increasing need for a more climate-friendly mobility and pose a challenge for the development of future powertrains. Hydrogen engines represent a suitable alternative for the heavy-duty segment. However, typical operation includes dynamic conditions and the requirement for high loads that produce the highest NOx emissions. These emissions must be reduced below the legal limits through selective catalytic reduction (SCR). The application of such a control system is time-intensive and requires extensive domain knowledge. We propose that almost human-like control strategies can be achieved for this virtual application with less time and expert knowledge by using Deep Reinforcement Learning. A proximal policy optimization (PPO) -based agent is trained to control the injection of Diesel exhaust fluid (DEF) and compared with the performance of a manually tuned controller. The performance is evaluated based on the restrictive emission limits of a
Itzen, DirkAngerbauer, MartinHagenbucher, TimoGrill, MichaelKulzer, Andre
Sustainable mobility is a pressing challenge for modern society. Electrification of transportation is a key step towards decarbonization, and hydrogen Fuel Cell Hybrid Electric Vehicles (FCHEVs) offer a promising alternative to Battery Electric Vehicles (BEVs), especially for long-range applications: they combine a battery system with a fuel cell, which provides onboard electric power through the conversion of hydrogen. Paramount importance is then given to the design and sizing of the hybrid powertrain for achieving a compromise between high performance, efficiency, and low cost. This work presents a Hardware-in-the-Loop (HIL) platform developed for designing and testing the powertrain layout of an FCHEV. The platform comprises two systems: a simulation model reproducing the dynamics of a microcar and a hardware system for the fuel cell hybrid electric powertrain. The former simulates the vehicle's behavior, while the latter is composed of a 2kW real fuel cell stack and a 100Ah Li-ion
Bartolucci, LorenzoCennamo, EdoardoCordiner, StefanoDonnini, MarcoGrattarola, FedericoMulone, Vincenzo
Electric and hybrid powertrains are steadily gaining popularity, showcasing their efficacy in reducing greenhouse gas emissions and pollution, particularly in urban environments. This also applies to medium and heavy-duty vocational trucks. Truck manufacturers have been expanding their electrified portfolio and some of them have already announced their plans to phase out fossil fuels. Vocational trucks are essential for the industry of commercial vehicles, represent an extremely heterogeneous class, and are often upfitted by third-party companies. In general, vocational trucks are designed for specific jobs. Typically, they are driven on short routes, but they may work for longer hours in comparison to freight transportation vehicles. Most importantly, among the broad category of vocational trucks, some vehicles greatly exploit power take-offs to drive auxiliary systems, like refuse trucks, utility trucks, cement trucks, and sweeper trucks. The benefits resulting from the kinetic
Beltrami, DanieleVillani, ManfrediIora, PaoloRizzoni, GiorgioUberti, Stefano
The aim of paper is to present the workflow of battery sizing for electric L7e-CU type vehicle. The intention is to use it as last-mile delivery multi-purpose vehicle. Based on legislation limits and pursuing the real-world driving cycle, major vehicle characteristics as total vehicle mass including payload and wheel size are determined. Vehicle total energy consumption is calculated knowing vehicle power in time. Accordingly, to selected gearbox ratio the electric motor nominal power-speed curve is defined as well as the nominal torque-speed curve. Applying vehicle acceleration dynamics involving limits considering resistive forces, acting on the vehicle, e.g. slope, friction, air drag, and total inertia, referred to the electric motor through the gearbox the electric motor over-load-ability characteristics are calculated. Next, the motor design is defined and optimized. Defining required vehicle range at given driving cycle and knowing the vehicle and all powertrain characteristics
Rupnik, UrbanVukotić, MarioManko, RomanAlić, AlenČorović, SelmaMiljavec, Damijan
Most military wheeled vehicles operate with a simplistic table-based transmission shift strategy. However, Allison Transmission Inc has created an innovative algorithm-based transmission shift strategy known as FuelSense®2.0 with DynActive® Shifting which optimizes gear selection by accounting for driver demand and vehicle load. This method of shifting has the potential to significantly improve fuel economy while only minimally degrading vehicle performance. In this study, FuelSense®2.0 with DynActive® Shifting was evaluated across three platforms which included the Family of Medium Tactical Vehicles (FMTV), and the Heavy Tactical Vehicles (HTV) Heavy Expanded Mobility Tactical Truck (HEMTT) and Palletized Loading System (PLS). The trucks were drive-cycle tested using both an environmentally controlled dynamometer laboratory and a real-world proving ground user trial
Zielinski, StevenBeiter, StevenMach, Newly
The U.S. Army initiated a shift towards electrifying and hybridizing its tactical vehicle fleet in alignment with its Climate Strategy and global automotive trends. Survey findings indicate a general desire by soldiers for the ability to opportunity charge electrified tactical vehicles, especially in austere locations, with a focus on solar recharging. This study extracts, cleans, and analyzes geo-location data from a training exercise at the National Training Center at Fort Irwin, CA to identify the drive cycles for over 400 tactical vehicles. These drive cycles were then used to estimate the energy consumption per vehicle. The analysis then identifies how much energy can be provided by a 300 W solar blanket, deployed when a vehicle is stationary. The study found that the 300 W solar blanket under ideal conditions could offset approximately 10 percent of the energy required by the average vehicle. As such, solar energy has the potential to be useful for providing small amounts of
Mittal, VikramMuraco, JohnKonopa, BridgetMayfield, LoganCrocker, MatthewRevnew, LukeMiller, Mark
Accurate estimation of vehicle energy consumption plays an important role in developing advanced energy-saving connected automated vehicle technologies such as Eco Approach and Departure, PHEV mode blending, and Eco-route planning. The present study developed a reduced-order energy model with second-order response surfaces and torque estimation to estimate the energy consumption while just relying on the drive cycle information. The model is developed for fully electric Chevrolet Bolt using chassis dynamometer data. The dyno test data encompasses the various EPA test cycles, real-world, and aggressive maneuvers to capture most powertrain operating conditions. The developed model predicts energy consumption using vehicle speed and road-grade inputs for a drive cycle. The accuracy of the model is validated by comparing the prediction results against track and road test data. The developed model was able to accurately predict the energy consumption for track drive cycles within the error
Goyal, VasuDudekula, Ahammad BashaStutenberg, KevinRobinette, DarrellOvist, GrantNaber, Jeffery
Test cycle simulation is an essential part of the vehicle-in-the-loop test, and the deep reinforcement learning algorithm model is able to accurately control the drastic change of speed during the simulated vehicle driving process. In order to conduct a simulated cycle test of the vehicle, a vehicle model including driver, battery, motor, transmission system, and vehicle dynamics is established in MATLAB/Simulink. Additionally, a bench load simulation system based on the speed-tracking algorithm of the forward model is established. Taking the driver model action as input and the vehicle gas/brake pedal opening as the action space, the deep deterministic policy gradient (DDPG) algorithm is used to update the entire model. This process yields the dynamic response of the output end of the bench model, ultimately producing the optimal intelligent driver model to simulate the vehicle’s completion of the World Light Vehicle Test Cycle (WLTC) on the bench. The results indicate that the
Gong, XiaohaoLi, XuHu, XiongLi, Wenli
Society is moving towards climate neutrality where hydrogen fuelled combustion engines (H2 ICE) could be considered a main technology. These engines run on hydrogen (H2) so carbon-based emission are only present at a very low level from the lube oil. The most important pollutants NO and NO2 are caused by the exhaust aftertreatment system as well as CO2 coming from the ambient air. For standard measurement technologies these low levels of CO2 are hard to detect due to the high-water content. Normal levels of CO2 are between 400-500 ppm which is very close or even below the detection limit of commonly used non-dispersive-infrared-detectors (NDIR). As well the high-water content is very challenging for NOx measuring devices, like chemiluminescence detectors (CLD), where it results in higher noise and therefore a worse detection limit. Even for Fourier-transformed-infrared-spectroscopy-analysers (FT-IR) it is challenging to deal with water content over 15% without increased noise. The goal
Jakubec, PhilippRoiser, Sebastian
Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined. Absolute and
Jacob, Jan D.
On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements. Meanwhile, the first generation of a complete portfolio of truck sizes has been developed and is available on the market. In these early applications, many compromises were made to overcome component availability, but today, the supply chain has evolved to address the specific needs of electric trucks. With that, optimization toward higher performance and lower costs is moving to the next level. For long-haul trucks, efficiency is a driving factor for the total cost of ownership (TCO) due to the importance of the energy costs [1]. Besides the propulsion system, other related systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the
Gajowski, DanielWenzel, WolfgangHütter, Matthias
In recent years, the urgent need to fully exploit the fuel economy potential of Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) has led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure in which an agent learns the optimal control strategy by interacting directly with an environment, making decisions, and receiving feedback in the form of rewards. Therefore, in this study, a new Soft Actor-Critic (SAC) agent, which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability. The proposed control strategy's potential was first assessed on the Worldwide harmonized Light-duty vehicles Test
Rolando, LucianoCampanelli, NicolaTresca, LuigiPulvirenti, LucaMillo, Federico
For battery-electric vehicles (BEVs), the climate control and the driving range are crucial criteria in the ongoing electrification of automobiles in Europe towards the targeted carbon neutrality of the automotive industry. The thermal management system makes an important contribution to the energy efficiency and the cabin comfort of the vehicle. In addition to the system architecture, the refrigerant is crucial to achieve high cooling and heating performance while maintaining high efficiency and thus low energy consumption. Due to the high efficiency requirements for the vehicle, future system architectures will largely be heat pump systems. The alternative refrigerant R-474A based on the molecule R-1132(E) achieved top performance for both parameters in various system and vehicle tests. An own-built energy efficiency tool was used to determine the possible energy reduction of R-474A in comparison to refrigerant alternatives that can be translated in a CO2 reduction of the thermal
Macrì, ChristianDe León, ÁlvaroFlohr, Felix
In response to global climate change, there is a widespread push to reduce carbon emissions in the transportation sector. For the difficult to decarbonize heavy-duty (HD) vehicle sector, hybridization and lower carbon-intensity fuels can offer a low-cost, near-term solution for CO2 reduction. The use of natural gas can provide such an alternative for HD vehicles while the increasing availability of renewable natural gas affords the opportunity for much deeper reductions in net-CO2 emissions. With this in consideration, the US National Renewable Energy Laboratory launched the Natural Gas Vehicle Research and Development Project to stimulate advancements in technology and availability of natural gas vehicles. As part of this program, Southwest Research Institute developed a hybrid-electric medium-HD vehicle (class 6) to demonstrate a substantial CO2 reduction over the baseline diesel vehicle and ultra-low NOx emissions. The development included the conversion of a 5.2 L diesel engine to
Wallace, JulianMitchell, RobertRao, SandeshJones, KevinKramer, DustinWang, YanyuChambon, PaulSjovall, ScottWilliams, D. Ryan
Driving schedule of every vehicle involves transient operation in the form of changing engine speed and load conditions, which are relatively unchanged during steady-state conditions. As well, the results from transient conditions are more likely to reflect the reality. So, the current research article is focused on analyzing the biofuel-like lemon peel oil (LPO) behavior under real-world transient conditions with fuel injection parameter MAP developed from steady-state experiments. At first, engine parameters and response MAPs are developed by using a response surface methodology (RSM)-based multi-objective optimization technique. Then, the vehicle model has been developed by incorporating real-world transient operating conditions. Finally, the developed injection parameters and response MAPs are embedded in the vehicle model to analyze the biofuel behavior under transient operating conditions. The results obtained for diesel-fueled light commercial vehicle (LCV) have shown better
Saiteja, PajarlaAshok, B.
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