Browse Topic: Energy management

Items (2,908)

Robust Predictive Cruise Control for Class 8 Trucks Considering Traffic Light Timing

2025-01-8033To be published on 04/01/2025

An implementation of a robust predictive cruise control method for class 8 trucks utilizing V2X communication with connected traffic lights is presented in this work. This method accounts for traffic signal phases with the goal of reducing energy consumption while maintaining reasonable travel speed and respecting safety concerns. Tightened constraints are created using a robust model predictive control (RMPC) framework in which constraints are modified so that the safety critical requirements are satisfied even in the presence of disturbances, while requiring only the expected bounds of the disturbances to be provided. In particular, variation in the actuator performance under different conditions presents a unique challenge for this application, which the approach applied in this work is well-suited to handle. The errors resulting from lower-level control and actuator performance are accounted for by treating them as bounded and additive disturbances on the states of the model used

Ellison, Evan, Ward, Jacob, Brown, Lowell, Bevly, David

Verification of the Impact of Coefficient of Drag Variation due to Natural Wind on Fuel Consumption based on Actual Driving Data

2025-01-8778To be published on 04/01/2025

It is often assumed that the actual fuel economy on public roads is affected by natural wind and that this could be contributing to discrepancy between catalog fuel economy and actual fuel economy, owing to the increased yaw angle and drag coefficient (CD). However, the impact of yaw characteristics alone on fuel economy during actual driving has not been verified or proven as it is difficult to obtain actual driving data under uniform conditions. For this reason, shape optimization is normally performed at zero-yaw through the aerodynamic development phases. In this paper, two vehicles with different yaw sensitivity characteristics are driven simultaneously, and fuel economy measurements are performed simultaneously with ambient airflow, environment, and vehicle conditions, and the results where the conditions of the two vehicles match are extracted to clarify the impact of the differences of yaw characteristics on fuel economy. The obtained results matched the values predicted by

Onishi, Yasuyuki, Nichols, Larry, Metka, Matt, masumitsu, Yasutaka, Inoue, Taisuke

Optimization method of phase change energy storage device for electric vehicle batteries based on numerical simulation

2025-01-8603To be published on 04/01/2025

Phase change energy storage devices are extensively utilized in latent heat thermal energy storage and hold significant potential for application in the thermal management of automotive batteries. By harnessing the high-density energy storage capabilities of phase change materials to absorb heat released by the batteries, followed by timely release and utilization, there is a substantial improvement in energy efficiency. This approach aligns with the objective of promoting low-carbon environmental protection and presents an opportunity to enhance the operational performance and energy utilization efficiency of electric vehicle batteries in low-temperature conditions. However, the thermal conductivity of medium and low temperature phase change materials is poor, leading to its inefficient utilization. This paper focuses on optimizing the structure of a phase change heat exchanger in a phase change energy storage device to improve its performance. A basic design of the phase change heat

Zhang, Haonan, Sun, Mingzhe, Zheng, Haoyun, Zhang, Tianming

European Initiatives addressing High efficiency and low cost electric motors for circularity and low use of rare resources

2025-01-8806To be published on 04/01/2025

The automotive industry is amidst an unprecedented multi-faceted transition striving for more sustainable passenger mobility and freight transportation. The rise of e-mobility is coming along with energy efficiency improvements, CO2 and non-exhaust emission reductions, driving/propulsion technology innovations, and a hardware-software-ratio shift in vehicle development for road-based electric vehicles. Current R&D activities are focusing on electric motor topologies and designs, sustainability, manufacturing, prototyping, and testing. This is leading to a new generation of electric motors, which is considering recyclability, reduction of (rare earth) resource usage, cost criticality, and a full product life-cycle assessment, to gain broader market penetration. This paper outlines the latest advances of multiple EU-funded research projects under the Horizon Europe framework and showcases their complementarities to address the European priorities as identified in the 2ZERO SRIA . The E

Armengaud, Eric, Ratz, Florian, Muñiz, Ángela, Poza, Javier, Garramiola, Fernando, Almandoz, Gaizka, Pippuri-Mäkeläinen, Jenni, Clenet, Stéphane, Messagie, Maarten, D’amore, Lea, Lavigne Philippot, Maeva, Rillo, Oriol, Montesinos, Daniel, Vansompel, Hendrik, De Keyser, Arne, Romano, Claudio, Montanaro, Umberto, Tavernini, Davide, Gruber, Patrick, Ran, Liaoyuan, Amati, Nicola, Vagg, Christopher, Herzog, Matic, Weinzerl, Martin

On-Road Investigation of Energy Saving Opportunity for Autonomous Light-Duty Vehicles through Automated Vehicle-Following in Safe Distance Scenarios

2025-01-8029To be published on 04/01/2025

Reducing aerodynamic drag through vehicle following is one of the energy reduction methods for connected and automated vehicles with advanced perception systems. This paper presents the results of an experimental investigation aimed at assessing energy reduction in manually driven light-duty vehicles through on-road tests of reducing the aerodynamic drag by vehicle following. This study provides insights into the effects of lateral positioning in addition to intervehicle distance and vehicle speed, and the profile of the lead vehicle. A series of tests were employed to analyze the impact of these factors, conducted under realistic driving conditions. The research encompasses various light-duty vehicle models and configurations, with advanced instrumentation and data collection techniques employed to quantify energy-saving potential. The study featured a two set of L4 capable light duty vehicles, including the Stellantis Pacifica PHEV minivan and Stellantis RAM Truck, examined in

Poovalappil, Aman, Robare, Andrew, Schexnaydre, Logan, Santhosh, Pruthwiraj, Bahramgiri, Mojtaba, Bos, Jeremy P., Chen, Bo, Naber, Jeffrey, Robinette, Darrell

A MIL/SIL Testing Approach for Predictive Energy Management Algorithms

2025-01-8583To be published on 04/01/2025

Energy management strategy is essential for HEV’s to achieve an optimum of energy consumption. With predictive energy management, taking future vehicle speed predicted from ADAS map information, in-vehicle navigation traffic flow status information, and current speed into account, one could anticipate a considerable improvement in energy-saving. The major validating approach widely adopted for energy management algorithms nowadays is real-world vehicle testing, of which the economic and time costs are relatively high. Moreover, with advanced algorithms featuring AI coming into light, putting forward higher requirement in the richness of test cases, the drawback in coverage of vehicle testing is revealed. This paper proposed a MIL/SIL testing approach for predictive energy management algorithms, providing an alternative to, and overcome the limitations of, vehicle testing. In the testing setup, random traffic would be generated by MATLAB based on real-time traffic condition queried from

Yan, Yue, Ma, Xiudan

Comprehensive gear shift schedule of heavy-duty commercial electric trucks based on dual axle driving

2025-01-8510To be published on 04/01/2025

A heavy-duty commercial electric truck is equipped with dual axles, with the middle axle driven by an electric motor and a three-speed transmission and the rear axle driven by an electric motor and a two-speed transmission. To consider the dynamics and economic performance of the whole vehicle, as well as the gear distribution characteristics in the vehicle operation, a comprehensive shifting law based on the cross-particle swarm algorithm is proposed. By establishing the longitudinal dynamics model of the truck, the optimal power shift schedule and the optimal economic shift schedule of each of the two transmissions are studied. Under the standard test conditions, an optimal gear control strategy based on the dynamic programming algorithm considering the shift interval is proposed, and the shift schedule for the standard conditions is derived through the hierarchical clustering method. Furthermore, with 100 km acceleration time and specific energy consumption as the objectives, a

Guo, Jun, Zhang, Yunqing, Wu, Jinglai

The development and real-time application of DP-based optimized A-ECMS algorithm for multi-mode series-parallel hybrid electric vehicles

2025-01-8589To be published on 04/01/2025

The hybrid electric drive system shows its great potential in the energy sustainability of the automotive industry. This paper investigates the improved adaptive equivalent consumption minimization strategy (A-ECMS) for a multi-mode series-parallel hybrid electric vehicle. First, a basic ECMS algorithm for the series-parallel vehicle is established, which considers the instantaneous optimal torque matching in the electric, serial hybrid, and engine driving modes. Then, Genetic Algorithms (GA) are used for offline global optimization of the equivalent factor and penalty function exponent. Under the condition that the future traffic information scenario is known, it is desired to realize the global optimal planning based on the combination of dynamic programming (DP) and ECMS. Therefore, the SOC, engine speed, and torque results calculated by the DP strategy are used as benchmarks to develop the improved SOC-AECMS and S-AECMS strategies, which better incorporate the advantages of the

Zhu, Jingyu, Han, Mengwei, Liu, Chongfan, Yang, Chenfan

European initiatives for User-Centric design of Electric Vehicle

2025-01-8807To be published on 04/01/2025

E-mobility is revolutionizing the automotive industry by improving energy efficiency, lowering CO2 and non-exhaust emissions, innovating driving and propulsion technologies, redefining the hardware-software-ratio in the vehicle development, facilitating new business models, and transforming the market circumstances for electric vehicles (EVs) in passenger mobility and freight transportation. Ongoing R&D action is leading to an uptake of affordable and more energy efficient EVs for the public at large through the development of innovative and user-centric solutions, optimized system concepts and components sizing, and increased passenger safety. Moreover, technological EV optimizations and investigations on thermal and energy management systems as well as the modularization of multiple EV functionalities result in range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under the

Ratz, Florian, Bäuml, Thomas, Kompara, Tomaž, Kospach, Alexander, Simic, Dragan, Jan, Petra, Möller, Sebastian, Fuse, Hiroyuki, Parades Barros, Esteban, Armengaud, Eric, Amati, Nicola, Sorniotti, Aldo, Lukesch, Walter

Model-Predictive Control for Heat Pump-Based Battery Thermal Management in Off-Road Autonomous Electrified Vehicles During Transient Operation

2025-01-8184To be published on 04/01/2025

The shift towards hybrid and electric powertrains in off-road vehicles aims to enhance mobility, extend range, and improve energy efficiency. However, heat pump-based thermal management systems in these vehicles continue to consume significant energy, impacting overall range and efficiency. Effective thermal management is essential for maintaining battery performance and safety, particularly in extreme conditions. Although high-fidelity models can capture the complex dynamics of heat pumps, real-time control within model-based optimization frameworks often depends on simplified models, which can degrade system performance. To address this, we propose a novel data-driven grey box control-oriented model (COM) that accurately represents the thermal dynamics of a vapor-compression refrigeration-based heat pump system. This COM is integrated into a model-predictive control (MPC) framework, optimizing thermal management during transient and burst-power operations of the battery pack. We

Sundar, Anirudh, Ghate, Atharva, Zhu, Qilun, Prucka, Robert, Ruan, Yeefeng, Figueroa-Santos, Miriam, Barron, Morgan

Energy consumption optimization of commercial electric bus in Indian city driving condition using two speed transmission

2025-01-8504To be published on 04/01/2025

ABSTRACT Currently automobile industries are shifting towards electric powertrains from conventional internal combustion engines. With increase in use of electric vehicle, more focus is to increase the driving range of vehicle. As of now, most of the OEMs are using single speed transmission in their electric buses. Single speed transmission is effective in road having less traffic condition but during heavy traffic condition (like Mumbai city application), performance of motor gets deteriorated. In heavy traffic condition (city application), operating points of motor goes into less efficiency regions which results in high energy consumption. It will also affect the regeneration. In this study, focus is on commercial vehicle like electric buses. If there is a need to increase driving range, energy consumption must be optimized. Thus, higher energy consumption in heavy traffic condition can be managed by using multiple gear ratio. With use of optimum gear ratio, motor operating points

Saurabh, Saurabh, Amancharla, Naga Chaithanya, Bhardwaj, Rohit, Gadve, Dhananjay

Fuel Consumption Estimation Using Spatio-Temporal Modeling and Traffic Flow Predictions: A Comparative Analysis

2025-01-8101To be published on 04/01/2025

Effective traffic management and energy-saving techniques are increasingly needed as metropolitan areas grow and traffic volumes rise. This work estimates fuel consumption over three selected routes in an urban context using spatio-temporal modeling essentially building on a previously developed approach in traffic prediction and forecasting. A weighted adjacency matrix for a Graph Neural Network (GNN) is constructed in the original approach which combines graph theory frameworks with travel times obtained from average speeds and distances between traffic count stations. Next, the traffic flow estimate uncertainty is measured using Adaptive Conformal Prediction (ACP) to provide a more reliable forecast. This work predicts fuel consumption under different scenarios by utilizing Monte Carlo simulations based on the expected traffic flows providing insights into energy efficiency and the best routes to take. The study compares passenger vehicles' and heavy-duty trucks' mean fuel

Patil, Mayur, Moon, Joon, Hanif, Athar, Ahmed, Qadeer

Machine Learning Based Lane Detection and Lateral Offset Estimation Model for Vehicle Following Applications

2025-01-8020To be published on 04/01/2025

Precisely understanding the driving environment and determining the vehicle's exact position are crucial for the safe operation of Autonomous Vehicles. In the vehicle following systems that offer higher energy efficiency by precisely following a lead vehicle, the relative position of the ego vehicle to lane center is a key measure to a safe automated speed and steering control. This article presents a novel Enhanced Lane Detection technique with centimeter-level accuracy in estimating the vehicle offset from the lane center using the front-facing camera. Leveraging state-of-the-art computer vision models, the Enhanced Lane Detection technique utilizes YOLO-V8 image segmentation, trained on a diverse real-world driving scenarios dataset, to detect the driving lane. To measure the vehicle lateral offset, our model introduces a novel calibration method using nine reference markers aligned with the vehicle perspective and converts the lane offset from image coordinates to real-world

Karuppiah Loganathan, Nirmal Raja, Poovalappil, Aman, Naber, Jeffrey, Robinette, Darrell, Bahramgiri, Mojtaba

Energy-Efficient Maneuvering of Connected and Automated Vehicles: NEXTCAR Phase II Results

2025-01-8385To be published on 04/01/2025

Onboard sensing and Vehicle-to-Everything (V2X) connectivity enhance a vehicle's situational awareness beyond direct line-of-sight scenarios. A team led by Southwest Research Institute (SwRI) demonstrated 20% energy savings by leveraging these streams on a 2017 Prius Prime as part of the first phase of the ARPA-E-funded NEXTCAR program. When combined with automation, these information streams can not only improve vehicle safety but also enhance energy efficiency further. In the second phase, SwRI demonstrated 30% energy savings over the baseline by leveraging connectivity with higher levels of automation. This paper summarizes the efforts to achieve 30% savings on a 2020 Honda Clarity PHEV. The vehicle was outfitted with the SwRI Ranger automated driving suite for perception and localization. Model-based control schemes with selective interrupt and control (SIC) were used to override stock vehicle controls and actuate the accelerator and brake pedals, and the electric power steering

Bhagdikar, Piyush, Gankov, Stanislav, Sarlashkar, Jayant, Hotz, Scott, Rajakumar Deshpande, Shreshta, Rengarajan, Sankar, Adsule, Kartik, Drallmeier, Joseph, D'Souza, Daniel, Alden, Joshua, Bhattacharjya, Shuvodeep

Research on the Control Strategy of Permanent Magnet Synchronous Motors with Reduced Rotor Stack Length in Hybrid System

2025-01-8563To be published on 04/01/2025

The key issue in the electromagnetic design of permanent magnet synchronous motors is the design of the rotor structure form of the motor. To achieve the goal of reducing the cost of the motor, this paper conducts electromagnetic design, optimal control calibration of the motor, and performance analysis for reducing the rotor lamination structure, and obtains the characteristics of the permanent magnet synchronous motor under this rotor structure. For the permanent magnet synchronous motor with reduced rotor stack length and one less motor temperature sensor, starting from vector control, the conditions for obtaining the maximum electromagnetic torque and the highest rotational speed are derived. Based on these conditions, the vector control strategies for the system operating under different working conditions are designed. At low speeds, the thermal loss of the stator winding is reduced with the maximum torque current ratio to improve the motor efficiency; as the rotational speed of

Jing, Junchao, Zhang, Junzhi, Yu, Pengfei, Liu, Yiqiang, Chen, Yingchao, Dai, Zhengxing

Design and Evaluation of a Conceptual Zero-Emission Truck Model Considering Aerodynamic Efﬁciency

2025-01-8784To be published on 04/01/2025

Emerging zero-emission-powertrain concepts for heavy trucks are providing opportunities to re-shape the vehicle for improved aerodynamics, leading to improved energy efficiency and range resulting from reduced drag. A multi-phase project was initiated to investigate the possibility of improving the aerodynamic efficiency of Class 8 trucks with internal-combustion, battery-electric, and hydrogen-fuel-cell powertrains. Early phases included a scaled-model wind-tunnel test that demonstrated the potential for up to 9% drag reduction from simple shape adaptations, with a follow-up CFD study providing guidance towards further optimization. This paper presents wind-tunnel-test results using a high-fidelity 30%-scale model of the final design concept, with comparison to a conventional North American Class 8 truck with a modern aerodynamic package and identical wheelbase. The study included the investigation of the new model along with individual parts such as air dams, underbody panels, grill

Ghorbanishohrat, Faegheh, McAuliffe, Brian, O'Reilly, Harrison

Lattice based Localized Energy Absorber for Improved Vulnerable Road User Performance for a Vehicle

2025-01-8723To be published on 04/01/2025

A passenger vehicle hood is designed to meet Vulnerable Road User (VRU) regulatory requirements and Consumer metric targets. Generally, hood inner design and its reinforcements, along with deformable space available under the hood are the main enablers to meet the Head Impact performance targets. However, cross functional balancing requirements like hood stiffness and packaging space constraints can lead to higher Head Injury Criteria (HIC) scores, particularly when secondary impacts are present. In such cases, a localized energy absorber is utilized to absorb the impact energy to reduce HIC within the target value. The current localized energy absorber solutions include the usage of flexible metal brackets, plastic absorbers etc. which has limited energy absorbing capacity and tuning capability. This paper focuses on usage of a novel 3D printed energy absorbers, based on various kind of lattice structures. These absorbers are either sandwiched between hood inner and the outer or are

Kinila, Vivekananda, Agarwal, Varun, V S, Rajamanickam, Tripathy, Biswajit, Gupta, Vishal

An Investigation of the Inter-Vehicle Distances and Lateral offsets on Aerodynamic Forces and Wake Structures of Vehicles Platooning

2025-01-8769To be published on 04/01/2025

In traffic scenarios, the spacing between vehicles plays a crucial role, as the actions of one vehicle can significantly impact others, particularly with regards to energy conservation. Accordingly, modern vehicles are equipped with inter-vehicle communication systems to maintain specific distances between vehicles. The aerodynamic forces experienced by both leading vehicles (leaders) and following vehicles (followers) are connected to the flow patterns in the wake region of the leaders. Therefore, improving our understanding of the turbulent characteristics associated with vehicles platooning is important. This paper investigates the effects of inter-vehicle distances on the flow structure of two vehicles: a small SUV as the leader and a larger light commercial van as the follower, using a Delayed Detached Eddy Simulation (DDES) CFD technique. The study focuses on three specific inter-vehicle distances: S = 0.28 L, 0.4L, and 0.5L, where S represents the spacing between the two

Mosavati, Maziar, Guzman, Arturo, Lounsberry, Todd, Fadler, Gregory

Development of Ceramic Humidity Regulator (CHR) Using Honeycomb Type PTC Heater to Improve Electric Vehicle Driving Range in Winter

2025-01-8177To be published on 04/01/2025

With Rapid growth of Electric Vehicles (EVs) in the market, challenges such as driving range, charging infrastructure, and reducing charging time needs to be addressed. Unlike traditional Internal combustion vehicles, EVs have limited heating sources and primarily uses electricity from the running battery, which reduces driving range. Additionally, during winter operation, it is necessary to prevent window fogging to ensure better visibility, which requires introducing cold outside air into the cabin. This significantly increases the power consumption for heating and the driving range can be reduced to half of the normal range. This study introduces the Ceramic Humidity Regulator (CHR), a compact and energy-efficient device developed to address driving range improvement. The CHR uses a desiccant system to dehumidify the cabin, which can prevent window fogging without introducing cold outside air, thereby reducing heating power consumption. A desiccant system typically consists of two

Hamada, Takafumi, Shinoda, Narimasa, Konno, Yoshiki, Ihara, Yukio, Ito, Masaki

Comparative Analysis of Mass Estimation Methods for Heavy-Duty Vehicles under Varying Payload Conditions

2025-01-8209To be published on 04/01/2025

Accurate mass estimation is essential for commercial heavy-duty vehicles (HDVs), as fluctuating payloads significantly impact energy consumption. Precise vehicle mass estimates enhance the accuracy of energy consumption models, leading to more effective energy management systems and performance optimization strategies. For example, improved energy estimates can lead to more optimized routing and refueling schedules, improving operational efficiency and reducing costs. In the context of electrification, accurate mass estimates can inform battery sizing, range predictions, and charging requirements, enabling optimized charge scheduling and seamless integration of electric HDVs into existing operations. While direct mass measurements may be obtained through external weight-in-motion or specialized onboard weighing systems, this paper focuses on methods that use data from Controller Area Network (CAN) systems for alternative real-time predictions. The challenge lies in identifying a method

Jayaprakash, Bharat, Eagon, Matthew, Fakhimi, Setayesh, Kotz, Andrew, Northrop, William

Smart Boosting: A Control Strategy for Optimized Energy Management with Boost Converter in Hybrid Electric Vehicles

2025-01-8580To be published on 04/01/2025

In hybrid electric vehicles (HEVs), optimizing energy management and reducing system losses are critical for enhancing overall efficiency and performance. This paper presents a novel control strategy for the boost converter in hybrid electric vehicles (HEVs), aimed at minimizing energy losses and optimizing performance by modulating to a higher boost converter voltage only when necessary. Traditional approaches to boost converter control often lead to unnecessary energy consumption by maintaining higher voltage levels even when not required. In contrast, the proposed strategy dynamically adjusts the converter's operation based on real-time vehicle demands, such as driver input, Engine Start-Stop (ESS) events, Active Electric Motor Damping (AEMD), entry and exit transitions for Engine Fuel Cut-Off (DFCO), Noise-Vibration-Harshness (NVH) events like lash-zone crossing and other specific operational conditions. The control strategy leverages predictive algorithms and real-time monitoring

Basutkar, Ameya, Berger, Daniel, Huo, Shichao, Sullivan, Claire, Tischendorf, Christoph

Evaluation of Different Powertrain Topologies for a Premium Plug-in Hybrid Electric Vehicle

2025-01-8531To be published on 04/01/2025

Plug-in hybrid electric vehicles combine the benefits of both battery electric and internal combustion engine drivetrains. There are multiple possibilities for hybrid configurations, each with its own advantages and disadvantages. In this study, two newly developed traction electric machines were employed alongside a gasoline engine in various hybrid configurations. These configurations, ranging from P1 to P4 and their combinations, were evaluated in terms of vehicle performance, energy consumption, and emissions. The impact of battery capacity was also examined. With a larger battery providing higher discharge power, the electric acceleration time significantly decreases from around 8.6 seconds to approximately 5.2 seconds as the battery capacity increases from 20 kWh to 40 kWh in configurations featuring two traction electric machines. In hybrid mode, the reduction in acceleration time is less pronounced, with a decrease of around 0.7 seconds compared to the configuration with a 20

Nguyen, Duc-Khanh, Tokat, Alexandra, Kristoffersson, Annika, Olsson, Jan-Ola

On the potentially misleading evaluation of CO2 emissions for hybrid-electric vehicles

2025-01-8537To be published on 04/01/2025

The adoption of hybrid electric vehicles (HEVs) is becoming more popular during the last few years due to government incentives and favourable legislation both for automotive companies and final users. This type of vehicle claims very low carbon dioxide emissions while eliminating the range anxiety associated with battery electric vehicles thanks to the on-board range extender being able to recharge the battery throughout the journey. Unfortunately, the low emissions values are more representative of the particular mathematical model implemented by the legislation than the measured real driving emissions. Specifically, the legislation does not take into account the CO2 embedded in production of the batteries or of the electrical energy stored in it. This work analyses these aspects by means of a numerical model of the BMW i3 94Ah vehicle. The results obtained are collected from simulations conducted over the Worldwide harmonized Light vehicles Test Cycle (WLTC) by using the commercial

Turner, James, Vorraro, Giovanni

Model-Based Evaluation of Hybrid Powertrains for a Light Duty Pickup Truck Application

2025-01-8532To be published on 04/01/2025

The ever-growing push for reducing GHG and NOx emissions has been challenging vehicle manufacturers globally. In the USA, multi-pollutant emissions standards finalized recently by EPA, for model years 2027 and later aim to reduce the CO2 emissions by 56% and 44%, respectively, for light and medium duty vehicles by 2032. The NMOG+ and NOx are also required to be reduced by 60 – 76% by 2032 from 2026 levels. Europe is also aiming to reduce CO2 emissions by 55% by 2030 from 1990 levels and 100% by 2035. To achieve such low levels of CO2 emissions, especially in the near-term scenario of limited EV sales, hybridization of conventional powertrains has found renewed interest. While hybrid powertrains add complexity, if optimized well for the application, they can offer best tradeoff between upfront cost, range, payload, performance, emissions and off-ambient operation. This study investigates the benefits and challenges of various hybrid architectures suitable for a pickup truck application

Fnu, Dhanraj, Correia Garcia, Bruno, Paul, Sumit, Joshi, Satyum, Franke, Michael

Powertrain components aging model selection for energy efficient vehicles: selection strategy and challenges

2025-01-8541To be published on 04/01/2025

The long-term performance of powertrain components in energy-efficient vehicles, particularly in Class 8 heavy-duty applications, is crucial for sustaining energy efficiency. However, these components degrade over time, leading to reduced performance and highlighting the need for appropriate aging models to estimate the impact of aging. This study aims to identify and select appropriate aging models for two critical powertrain components: battery and electric machine. Through a comprehensive literature review, the primary aging processes, key influencing factors, and available aging models for these components are identified. A selection matrix is established, considering model complexity, accuracy, and the volume of data required to maintain the desired precision for the powertrain component models. Based on the selection matrix, an appropriate model is chosen for the vehicle’s battery. This model was selected for its ability to effectively capture the aging process and estimate

Rownak, Md Ragib, Hanif, Athar, Ahmed, Qadeer, Fahim, Muhammad Qaisar, Anwar, Hamza, Li, Hui, Le, Dat, Nelson, Matthew

Cost Analysis of Battery Electric and Fuel Cell Powertrains for Class 8 Heavy-Duty Trucks in Real-World Scenarios: A 2024, 2035 and 2050 Perspective

2025-01-8592To be published on 04/01/2025

This study evaluates the performance of alternative powertrains for Class 8 heavy-duty trucks under a variety of real-world driving conditions, cargo loads, and operating ranges. Energy consumption, greenhouse gas emissions, and the Levelized Cost of Driving (LCOD) were assessed for different powertrain technologies in 2023, 2035, and 2050, considering anticipated technological advancements. The analysis was conducted using simulation models that accurately reflect vehicle dynamics, powertrain components, and energy storage systems, leveraging real-world driving data. The Argonne National Laboratory's POLARIS, SVTrip, Autonomie, and TechScape software were used in an integrated simulation workflow for this analysis. Additionally, a sensitivity analysis was conducted on fuel and battery costs to understand their impact on economic outcomes. The study considered a hydrogen cost of $4/kg in 2035 and 2050, three AEO2023 low, medium, high diesel cost scenarios, and electricity costs ranging

Mansour, Charbel, Bou Gebrael, Julien, Kancharla, Amarendra, Freyermuth, Vincent, Islam, Ehsan Sabri, Vijayagopal, Ram, Sahin, Olcay, Zuniga, Natalia, Nieto Prada, Daniela, Alhajjar, Michel, Rousseau, Aymeric, Borhan, Hoseinali, El Ganaoui-Mourlan, Ouafae

Activity and Performance of Zero and Near-Zero Emissions Port Equipment for Emissions Reduction in the Maritime Sector

2025-01-8539To be published on 04/01/2025

Medium-duty (MD) and heavy-duty (HD) vehicles and off-road equipment make one of the most important contributions to the emissions inventory for both urban pollutants and greenhouse gases. Reducing the emissions contribution from these sources has been a focus of regulations and incentive programs over the past few years. The number of plug-in and electric vehicle/equipment models in the MD, HD, and off-road equipment categories has significantly expanded in recent years. Along with that, a growing number of fleets are deploying or are interested in deploying electric vehicles such as port-related equipment, transit buses, school buses, trucks, and other off-road equipment. With this rapid growth of electric vehicles in the market, reliable operation and performance data on electric MD and HD vehicles/equipment is needed to provide insights on usage and to support the ongoing research into the future deployment. The objective of this study is to collect and analyze activity data from a

Frederickson, Chas, Vu, Alexander, makki, Maedeh, Johnson, Kent, Durbin, Tom, Burnette, Andrew, Huang, Eddy, alvarado, Erica, Rao, Leela

Meteorolgical Aspects of the Operational Design Domain -- Enhancing Road and Rail Safety and Efficiency through Integrated Wind, Weather, and Motion Sensing Technology

2025-01-8100To be published on 04/01/2025

In recent years, integrated sensor systems have significantly advanced environmental monitoring, providing essential insights for addressing various environmental challenges. This paper introduces a novel wind, weather, and motion sensor, designed primarily for automotive environments but also applicable to rail systems. The paper explores how these sensors enhance the safety and efficiency of vehicles by detecting critical environmental parameters. Key concepts such as the Operational Design Domain (ODD) and Operational Domain (OD) are discussed, emphasizing their importance in the deployment of connected, automated, and autonomous vehicles. The distinction between ODD and OD is illustrated using real-world examples, highlighting the necessity for advanced detection and response capabilities in complex driving scenarios. Furthermore, the paper delves into the significance of road-related atmospheric conditions like temperature, humidity, pressure, and wind. Current state-of-the-art

Feichtinger, Christoph Simon

Leveraging Traffic-in-the-Loop Simulations to Assess the Impact of Traffic on Vehicle Energy Consumption

2025-01-8054To be published on 04/01/2025

The advancements in vehicle connectivity and the increased level of driving automation can be leveraged for the development of advanced driver assistance systems (ADAS) that improve driver safety and comfort while optimizing the energy consumption of the vehicle. In the development phase of energy-efficient ADAS, modeling and simulation are used to assess the potential benefits of these technologies on energy consumption. However, there is a lack of standardized simulation or test frameworks to quantify the benefits. Moreover, the driving scenario and the traffic conditions are often not explicitly modeled when simulating energy-efficient ADAS, even though they have a major impact on the attainable energy benefits. This paper presents the development and implementation of a closed-loop traffic-in-the-loop simulator designed to evaluate the performance of vehicles under realistic traffic conditions. The primary objective is to assess how varying traffic conditions influence vehicle

Grano, Elia, Villani, Manfredi, Ahmed, Qadeer, Carello, Massimiliana

Demonstration of Model Predictive Control to optimise cabin thermal comfort in a battery electric vehicle

2025-01-8145To be published on 04/01/2025

The focus on thermal system efficiency has increased with the introduction of electric vehicles (EV) where the heating and cooling of the cabin represents a major energy requirement that has a direct impact on vehicle range in hot and cold ambient conditions. This is further exacerbated during heating where EVs do not have an engine to provide a source of heat and instead use stored electrical energy from the battery to heat the vehicle. This paper considers two approaches to reduce the energy required by the climate control and hence increase the range of the vehicle. The first approach considers minimizing the energy to keep the passengers comfortable, whilst the second approach optimizes the heating and ventilation system to minimize the energy required to achieve the target setpoints. Finally, these two approaches are combined to minimize both the passenger’s demand and the energy required to meet the demand. This paper covers the development process from simulation to

Fussey, Peter, Dutta, Nilabza, Milton, Gareth, Ma, He

The impact of GCI engines on energy consumption and performance of longhaul trucks in the US and China

2025-01-8396To be published on 04/01/2025

This paper focuses on the impacts of GCI engines and automated driving technologies on heavy-duty long-haul trucks in both the Chinese and US markets. The study examines various aspects, including vehicle performance requirements, fuel consumption, emissions, and ownership costs, and their influence on the adoption and impact of these technologies. Furthermore, the GCI engine’s cost advantages in the Chinese market are noteworthy. Its lower urea cost effectively offsets its higher energy expenditure, highlighting its potential for cost-effective overall operation. Additionally, the GCI engine holds promise in the medium-duty trucking sector due to forthcoming low NOx requirements and the potential for cost reductions in hybrid powertrains. Medium-duty trucks, characterized by transient driving patterns and shorter daily distances, can significantly reduce energy demands, thereby diminishing the costs associated with hybrid components. The integration of GCI engines into heavy-duty long

Nieto Prada, Daniela, Vijayagopal, Ram, Yan, Ziming, Sari, Rafael, He, Xin

Knock Assessment in Wankel Rotary Engine Adopting Low Octane Rating Fuels

2025-01-8452To be published on 04/01/2025

Series hybrid vehicles, equipped with internal combustion range extenders, are a promising solution for carbon-free transportation. In this application, zero net carbon emissions can be achieved only using renewable fuels. Fischer-Tropsch-derived e-gasolines allow for high energy density and safe fuels. However, Fischer-Tropsch fuels must undergo several processing stages to reach current engine-grade octane ratings, negatively affecting the synthesis's profitability and energy efficiency. Gasoline engine technologies capable of operating with low-octane fuels could allow the adoption of unprocessed Fischer-Tropsch gasoline. The rotary Wankel engine design suits range extenders thanks to its high power-to-size ratio. In this study, the knocking tendency of homogenous charge spark-ignition rotary Wankel engines is numerically assessed through Chemkin-Pro spark-ignition engine zonal model for knock assessment. Rotary Wankel engines are modeled by providing the corresponding time

Brunialti, Sirio, Vorraro, Giovanni, Turner, James, Sarathy, Mani

Modeling and Simulation analysis of an electric vehicle in normal and hot ambient conditions: energy consumption and driving range

2025-01-8151To be published on 04/01/2025

With better performance and usage of clean and renewable energy, electric vehicles have ushered in more and more consumers’ favor nowadays. However, insufficient driving range especially in hot and cold ambient conditions still greatly restricts the extensive application of electric vehicles. This paper presents a methodology of establishing mechanics-electricity-thermodynamics coupled full vehicle model in AMESim to investigate the energy consumption and driving range of an electric vehicle in normal and hot ambient conditions. Full vehicle energy consumption test was carried out in the climate chamber to check the accuracy of simulation results. Firstly, basic framework of the full vehicle model established in AMESim was introduced. Next, modeling details of sub-systems including vehicle dynamic system, electrical system, coolant circuit system, air-conditioning system and control strategy were illustrated. Then, full vehicle energy consumption tests were carried out in 23℃ and 38

ZHOU, Shuai, Liu, Huaiju, YU, Huili, Yan, Xu, Yan, Junjie

Study on Energy Consumption and Emission Characteristics of EHC Coupled DOC+SDPF+SCR-ASC System under WLTC and RDE

2025-01-8498To be published on 04/01/2025

With the tightening of emission regulations, electrically heated catalytic converters (EHC) are an important technical solution for diesel vehicles to address the challenges of cold start and RDE emission reduction. This paper investigates the impact of EHC coupled exhaust aftertreatment system (DOC+SDPF+SRR-ASC) on the energy consumption and emission characteristics of light-duty diesel vehicles based on the World Light Vehicle Test Cycle (WLTC) and Real Driving Emissions (RDE). The research results show that under WLTC conditions, compared to EHC off, the time for the SDPF inlet temperature to reach 180 ℃ when EHC on is 44 seconds earlier. The CO emission value of diesel vehicles is 67.5 mg/km, the THC emission value is 49.8 mg/km, the NMHC emission value is 42.5 mg/km, and the NOx emission value is 28.7 mg/km, which is far below the limit requirements of CHINA VI B. Among them, the average urea injection rate increased by 1.1 mg/s, and the overall NOx conversion efficiency increased

Kang, Lulu, Zhao, Zhiguo, Lou PhD, Diming

Design and Optimization Strategies for Multi-Gear Power Split Hybrid Systems Based on Topological Tree Graphs

2025-01-8379To be published on 04/01/2025

Energy-efficient configuration schemes are critical to the fuel economy and performance of hybrid vehicles. Single planetary gear (PG) configurations are highly integrated, simple and reliable, but have limited fuel saving potential. To overcome these problems, a new multi-gear power split (PS) powertrain has been proposed due to its high efficiency and excellent overall performance. Only one PG and one synchronizer are required. In order to systematically explore all possible designs of multi-gear PS hybrid designs, this paper proposes a topological tree graph method: 1) inspired by the "D" matrix automatic modeling method, a new configuration tree matrix is proposed, which is used to complete the isomorphism determination, mode feature classification, and dynamics modeling; a design synthesis method for the multi-gear PS configuration is investigated; 2) a new near-optimal energy management strategy, the Improved Rapid-DP (IR-DP), is proposed for the fast computation of the near

zou, yunge, zhang, yuxin, Yang, Yalian

Lookahead Information based Predictive Cruise Controller for Energy Efficient Powertrain Operation of Heavy-Duty Electric Trucks

2025-01-8031To be published on 04/01/2025

The shift towards electric heavy-duty trucks marks a significant move in sustainable freight transportation, aiming to reduce carbon emissions and decrease reliance on fossil fuels. While these trucks offer enhanced powertrain efficiency and lower operating costs, maximizing their potential requires a focus on minimizing energy consumption during operation. Efficient energy management through optimized driving strategies is essential to extend the battery life and reduce the overall environmental impact of electric trucks in long-haul logistics. This research paper introduces a predictive cruise controller that combines look-ahead information with the powertrain controller to generate an optimal speed profile for electric trucks. By optimizing the vehicle’s speed based on upcoming road conditions, the system enhances the energy efficiency of the entire powertrain, leading to more sustainable and cost-effective truck operation. The Predictive Cruise Controller (PCC) optimizes electric

Safder, Ahmad Hussain, Villani, Manfredi, Khuntia, Satvik, Nelson, James, Meijer, Maarten, Ahmed, Qadeer

Electric Vehicle Dynamic Operation Simulation with Data-driven and Physical-based Models

2025-01-8604To be published on 04/01/2025

Aiming at the complexity of the dynamic operation simulation of electric vehicles (EVs), this paper proposes a dynamic operation simulation model that integrates data-driven and physical-based principles. This model framework combines the advantage of interpretability from the physical model while leveraging the strength of rapid simulation under dynamic operating conditions of the electric vehicles from the data-driven model. The physical model part covers key aspects such as vehicle dynamics modeling, regenerative braking system, temperature model, and battery state estimation model. The data-driven part extracts key features and labels based on actual vehicle operation data, and establishes a capacity-life prediction model for the power pack of an electric vehicle by using the long-short-term memory model (LSTM). By combining the physical model with a data-driven approach, this model effectively simulates dynamic changes in vehicle cabin temperature, battery pack temperature, and

Jing, Hao, HU, Jianyao, Ouyang, Jianheng, Ou, Shiqi(Shawn)

Impact of Hybrid Electric Vehicles on Energy Consumption and Emission Reduction for Agricultural Applications

2025-01-8540To be published on 04/01/2025

As the agricultural industry seeks to enhance sustainability and reduce operational costs, the introduction of mild hybrid technology in tractors presents a promising solution. This paper focuses on downsizing internal combustion (IC) engine, coupled with integration of electric motor, to reduce fuel consumption and meet stringent emission regulations while maintaining power requirement for agricultural applications in India. The hybridization aims to deliver instant power boosts during peak loads and capitalizes on energy recovery during part loads and braking. Furthermore, the idle avoidance feature minimizes fuel consumption during periods of inactivity thus significantly improving fuel efficiency. The hybridization also aims to hybridize auxiliary systems for flexible power management, enabling operation of either engine, auxiliaries, or both as needed. A newly developed hybrid supervisory control prototype efficiently manages the electric power and the mechanical power, enabling

Prasad, Lakshmi P., PS, Satyanarayana, Paygude, Tejas, Gangsar, Purushottam, Thakre, Mangesh, Choudhary, Nagesh

Optimization-Oriented Adaptive Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Electric Vehicles Based on Power

2025-01-8552To be published on 04/01/2025

Fuel economy and the ability to maintain the state of charge (SOC) of the battery are two key metrics for the energy management of a full-power fuel cell hybrid vehicle fitted with a small-capacity battery pack. To achieve stable maintenance of SOC and near-optimal fuel consumption, this paper proposes an adaptive equivalent consumption minimization strategy (PA-ECMS) based on power prediction. The strategy realizes demand power prediction through a hybrid deep learning model, and periodically updates the optimal equivalent factor (EF) based on the predicted power to achieve SOC convergence and ensure fuel economy. Simulation results show that the hybrid deep learning network model has high prediction accuracy with a root mean square error (RMSE) of only 0.733 m/s. Compared with the traditional ECMS based on SOC feedback, the PA-ECMS effectively maintains the battery SOC in a more reasonable range, reduces the situation of the fuel cell directly charging the power cell in the high

Gao, Xinyu, Ju, Fei, Chen, Gang, Zong, Yuhua, Wang, Liangmo

On-Vehicle Optimum Route Selection for a Plug-in Hybrid Electric Vehicle

2025-01-8388To be published on 04/01/2025

This paper presents a methodology to optimally select between routes proposed by mapping software. The objective of the optimization is to make the best trade-off between travel time and energy consumption when deciding between different routes. The method runs on vehicle and uses an Intelligent driver model to convert the data from the mapping software into a vehicle speed & torque profile, then uses a Reduced Order Energy model to find the vehicle energy consumption for each route. Weightings are applied to the difference in energy and travel time for each route compared to the primary route. The PHEV used in this investigation is the Stellantis Pacifica. Results support energy savings of up to 20% compared to the primary route, which depends on the routes and initial battery State of Charge (SOC

Robare, Andrew, Poovalappil, Aman, Udipi, Anirudh, Bhure, Mayur, Bahramgiri, Mojtaba, Robinette, Darrell, Naber, Jeffrey, Chen, Bo

Increasing Energy Efficiency of Vehicles Using Combined Electromechanical Engine-Transmission Systems

2025-01-8527To be published on 04/01/2025

The emergence of electric and hybrid vehicles with separate axle or wheel drives offers the potential to control torque distribution between the front and rear wheels. The stepless, smooth control of electric motors enables the continuous operation of both axles, even on roads with high rolling resistance. This ensures an optimal torque distribution, enhancing the vehicle's overall efficiency. A synergistic effect in hybrid vehicles can be achieved by optimizing the control of both the internal combustion engine and electric motors, minimizing energy consumption during movement. Analysis indicates that hybrid vehicles' dynamic properties and handling can be improved by using the internal combustion engine for steady-state driving and electric energy for acceleration. Maintaining the internal combustion engine at a constant speed is a key factor in increasing energy efficiency, making the vehicle more responsive during acceleration. The proposed method facilitates the selection of the

Podrigalo, Mikhail, Kholodov, Mykhailo, Dubinin, Yevhen, MOLODAN, ANDRII, SERGYJOVYCH, Oleksandr Polianskyi, Kaidalov, Ruslan, Abramov, Dmytrii

Energy Savings and Range Extension from Aerodynamic Improvements of Emerging Zero-Emission Heavy Vehicle Concepts

2025-01-8787To be published on 04/01/2025

An energy-use analysis is presented to examine the potential energy-savings and range-extension benefits of aerodynamic improvements to tractors and trailers used in commercial transportation. The impetus for the study was the observation of aerodynamically-redesigned/optimized tractor shapes of emerging zero-emission tractors that have the potential for significant drag reduction over conventional aerodynamic tractors. Using wind-tunnel test results, a series of aerodynamic performance models were developed representing a range of tractor and trailer combinations. From current-day day-cab and sleeper-cab tractors to aerodynamically-optimized zero-emission cab concepts, paired with standard dry-van trailers or low-drag trailer concepts, the study examines the potential of implementing various fleet configurations for different operational duty cycles. An energy-use analysis was implemented to estimate the energy-rate contributions associated with inertial accelerations, grade forces

McAuliffe, Brian, Ghorbanishohrat, Faegheh

Series and IMMD+: Performance Comparison and Analysis of Hybrid Vehicles with Additive Clutches

2025-01-8538To be published on 04/01/2025

The series-parallel hybrid system has become an important development route for hybrid vehicles. To enhance energy efficiency of series-parallel hybrid system, this paper investigates and compares the effects of increasing the clutch or adding the gear ratio at different power source position on the performance of the vehicle. Firstly, the effect of adding clutches or gears at different is analyzed，and the possible working modes with the addition clutch or gear ratios of different power source positions are investigated. Secondly, multi-objective particle swarm optimization (MOPSO) algorithm is used to solve the transmission ratio of the new gears of the improved configuration with fuel consumption and acceleration time as the design objectives, which provides a foundation for the subsequent comparative study of different configurations. Moreover, the fuel economy performance of the producing series-parallel configuration was evaluated using a rapid dynamic programming approach with

zhang, yuxin, zou, yunge, Yang, Yalian

Computational Fluid Dynamics Analysis of Gearbox Churning Loss and Oil Splash Characteristics in Electric Vehicle Drive Units

2025-01-8182To be published on 04/01/2025

The efficient operation of electric vehicles (EVs) heavily relies on the proper lubrication of the E-drive unit components, particularly the transmission gears and bearings. Inadequate oil supply can lead to mechanical failures, while excessive oil can increase power loss due to churning. This study focuses on utilizing Computational Fluid Dynamics (CFD) simulations to analyze the impact of drive speed, oil level and temperature on gear churning loss in E-drive units. The research also investigates the influence of a baffle plate on power loss and oil splash characteristics. The simulations, conducted using the volume of fluid (VOF) method in Simerics-MP+, consistently illustrate a reduction in power loss with rising oil temperature and reveal decreased gear churning loss with a baffle plate, especially under high-speed conditions, highlighting its potential for enhancing energy efficiency in EVs. Additionally, post-processing analysis of oil splash patterns sheds light on the

Kumar, P. Madhan, Motin, Abdul, Pandey, Ashutosh, Ganamet, Alain, Maiti, Dipak, Gao, Haiyang, Ranganathan, Raj

Machine Learning-Based Digital Twin for Optimizing Automotive Components

2025-01-8206To be published on 04/01/2025

This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the Electric Lubrication Oil Pump (ELOP), a crucial component within a vehicle's powertrain system. The proposed ELOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This estimation approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the digital twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's

Khan, Jalal, D'Alessandro, Stefano, Tramaglia, Federico, Fauda, Alessandro

Downsizing 12 volts battery for EV using effective energy management strategies when vehicle is inactive

2025-01-8192To be published on 04/01/2025

On electric vehicle the low voltage (nominal 12 volt) battery serves mostly as an energy storage buffer for supporting features and actuators on the 12 volts power supply network. The power management strategies significantly influences the thermal management of the vehicle especially in power critical states. Within an EV, unlike an internal combustion engine car, as there is no cranking requirement needed to be supported by this battery, it presents a significant opportunity for downsizing. This can save from 10 kg-15 kg which could add up to 1 mile of range in combined cycle. In a premium car there are a significant number of features which inhibits the car to go into “deep sleep” and hence remains on a “stand-by” mode of operation. During this period of stand-by the low voltage energy storage system need to be sized for up to 0.4 W of continuous power drain. To sustain longer periods of stand-by mode the low voltage battery needs to have enough stored energy to maintain the

Dutta, Nilabza, Overs, Sheldon

Systematic Design Considerations of Motor Selections for EV Powertrain

2025-01-8508To be published on 04/01/2025

Electric vehicles (EVs) have gained intense attraction during recent years for the energy saving they can provide over internal combustion engines. EV powertrain is a complex system with different electromagnetic, Electrical and mechanical components including motor, gear box, battery and transmission line. These components are interconnected creating the overall powertrain architecture. As a result, instead of designing sub-optimized or over-compensated components with individual design specifications, systematic design optimization including other related power train components should be considered when defining a new EV. As one of the most important design choices in the powertrain design cycle, motor selection is conventionally performed according to given automative requirements. Motor-related powertrain design parameters like gear ratio, power output ratio between different axles, are excluded from the motor design process. In this presentation, two comparative studies are

Movahed, Ehsan, Godbehere, Jonathan, jia, Yijiang

Comparative study of emissions and energy consumption of battery electric and hydrogen fuel cell electric HDVs for production and use phases

2025-01-8599To be published on 04/01/2025

The depletion of fossil fuels and the emergence of global warming propel public sectors to explore alternative energy such as renewable electricity and hydrogen to reduce greenhouse gas (GHG) emissions. Numerous studies have demonstrated substantial environmental benefits of electric light-duty vehicles. However, research focusing on heavy-duty vehicles is still relatively scarce, and the transition to zero-emission heavy-duty trucking is facing enormous technical and economic challenges. The present work focuses on decarbonised heavy-duty vehicles (HDVs), including battery electric (BE) and gaseous hydrogen fuel cell electric (FCE) trucks, to identify contributions and implications of the eco-friendly trucks for achieving the net zero emissions target. To this end, the study uses the SimaPro software package with wildly accepted Ecoinvent database to investigate environmental implications during the vehicle manufacturing and assembly stage based on UK grid mix. A comparative analysis

Zhao, Jianbo, Li, Hu, Babaie, Meisam, Li, Kang

Optimal Energy Management of Parallel Electric-Hydraulic Hybrid Vehicles based on Dynamic Programming and Recurrent Neural Networks

2025-01-8582To be published on 04/01/2025

This paper presents an approach for optimal energy management in parallel electric-hydraulic hybrid vehicles using recurrent neural networks trained through dynamic programming results. While electric vehicles are increasingly recognized for their sustainability and zero tailpipe emissions, their implementation faces critical challenges, especially in heavy-duty applications. The low power density of lithium-ion batteries limits their ability to effectively capture regenerative braking energy, particularly during short braking periods. In addition, high peak current loads due to heavy torque demands can accelerate battery aging. To address these challenges, a hybrid vehicle that combines electric and hydraulic systems has been proposed in the literature. This vehicle integrates a hydraulic pump/motor and a hydro-pneumatic accumulator with an electric powertrain, aiming to achieve both high power density and energy density while mitigating peak loads on the battery. Like other hybrid

Taaghi, Amirhossein, Yoon, Yongsoon

Coupled Routing and Charge Schedule Optimization of Electrified Delivery Truck Fleets Feasibility Analyses

2025-01-8602To be published on 04/01/2025

Electrifying truck fleets has the potential to improve energy efficiency and reduce carbon emissions from the freight transportation sector. However, the range limitations and substantial capital costs with current battery technologies imposes constraints that challenge the overall cost feasibility of electrifying fleets for logistics companies. In this paper, we investigate the feasibility via coupled routing and charge scheduling optimization of a delivery fleet serving a large urban area. To this end, we first build an improved energy consumption rate model for a Class 7-8 electric and diesel truck using a data-driven approach of generating energy consumption data from powertrain simulations on numerous drive cycles. We then conduct several analyses on the impact of battery size, cost, and electricity prices on the feasibility of fleet electrification at different penetration levels, considering availability of fast charging at the depot. Findings indicate that at typical energy

Wendimagegnehu, Yared Tadesse, Ayalew, Beshah, Ivanco, Andrej, Hailemichael, Habtamu

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