Browse Topic: Energy consumption

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Improving Speed Trajectory Optimization for Electric Vehicles with Pre-Calculated Energy Maps and Dynamic Profile Discretization2025-01-0318To be published on 07/02/2025
Ongoing research and development in the field of electric vehicles (EVs) have resulted in a continuous expansion of their range. Additionally, advancements in vehicle connectivity have created new opportunities for intelligent driving assistance and energy optimization, particularly through the use of cloud data. However, the integration of eco-driving assistance with numerical optimization of speed trajectories remains challenging due to the high computational demands of these methods. To address this challenge and make such a system feasible for integration into vehicle systems, the computational effort required for an optimized driving trajectory must be minimized. This paper presents a method to accelerate speed trajectory optimization using pre-calculated energy and time consumption maps. For this purpose, a dynamic discretization of the anticipated driving profile is applied. Initial results show a substantial reduction in computation time, varying with different scenarios
Schilling Johnson, Rene, Henke, Markus
Technical Paper
Applying Real World Traffic Data on Machine Learning Methods for Graph Based Cooperation Strategies of Automated Vehicles2025-01-0286To be published on 07/02/2025
With the increasing distribution of smart mobility systems, automated & connected vehicles are more and more interacting with each other and with smart infrastructure using V2X-communication. Hereby, the vehicles' position, driving dynamics data, or driving intention are exchanged. Previous research has explored graph-based cooperation strategies for automated vehicles in mixed traffic environments based on current V2X-communication standards. Thereby, the focus is set on cooperation optimization and maneuver negotiation. These strategies can be implemented through both centralized and decentralized computational approaches and are conflict-free by design. To enhance these previously established cooperation models, real-world traffic data is used to derive vehicle trajectories, providing a more accurate representation of actual traffic scenarios in order to enhance the practical application of the described methodology. Additionally, machine learning algorithms are employed to train
Flormann, Maximilian, Meyer, Felix, Henze, Roman
Technical Paper
Optimized Cabin Heating Strategy for Battery Electric CEP Vehicles2025-01-0263To be published on 07/02/2025
Electromobility is gaining importance in the courier, express and parcel (CEP) sector, as parcel service providers increasingly rely on zero-emission vehicles to improve their CO₂ footprint. A common drawback of battery electric vehicles is their reduced range under cold operating conditions, due to the increased energy demand for cabin heating. Another CEP-specific factor influencing both energy consumption and cabin comfort is the frequent opening of doors during parcel delivery. Additionally, during delivery phases, the cabin cools down in the driver’s repeated absence from the cabin, as the heating is inactive. Nonetheless, a sufficient level of thermal comfort must be maintained during the driving phases between delivery stops. This paper presents an optimization-based strategy for the cabin heating of battery electric CEP vehicles. The objective is to maximize cabin comfort during driving phases while maintaining efficient energy consumption. For this purpose, a nonlinear model
Rehm, Dominik, Krost, Jonathan, Meywerk, Martin, Czarnetzki, Walter
Technical Paper
Modular Thermal Management Framework for Electric Drive System Development2025-01-0262To be published on 07/02/2025
The automotive industry is undergoing a major shift from internal combustion engines (ICE) to hybrid (HEV) and battery-electric vehicles (BEV), which has led to significant advancements and increased complexity in drivetrain design and thermal management systems. This complexity reflects the growing need to optimize energy efficiency, extend vehicle range, and ensure system reliability in modern electric vehicles. At the Institute of Automotive Engineering, a specialized synthesis tool for drivetrain optimization is used to identify the best drivetrain configurations based on specific boundaries and requirements. Building up on this toolchain a modular and adaptable thermal management framework has been developed, addressing another critical aspect of vehicle and drive development: efficient thermal circuit layout and its impact on energy consumption and overall system reliability. The thermal framework emphasizes the dynamic interactions between key components, such as electric
Notz, Fabian, Sturm, Axel, Sander, Marcel, Kässens, Christoph, Henze, Roman
Technical Paper
Experimental Quantitative Analysis of Spray Velocity Field Characteristics of Four Compression-Ignition Engine Oxygenated Alternative Fuels03-18-03-002105/10/2025
As the suitable substitutes for diesel in compression-ignition (CI) piston engines, hydrotreated vegetable oil (HVO), polyoxymethylene dimethyl ethers (PODEs), and bio-aviation fuel (BAF), among other oxygenated alternative fuels have been widely recognized due to higher cetane values. To explore the in-cylinder fuel spray dynamics and subsequent fuel–air entrainment of these fuels, experimental studies on near-field and full-field spray characteristics were carried out by the diffuser back-illumination imaging (DBI) method within a constant-volume chamber. The local velocity was inferred by momentum flux conservation and Gaussian radial profile assumption, and the dimensionless Jet number was introduced to qualify the strength of interaction within two-phase flow. It was found that the initial spray transitions from a “needle” to a larger spray head structure as injection pressure rises, especially with PODE3-5 exhibiting a stable “mushroom” structure due to its higher surface tension
Chen, Houchang, Jiang, Junxin, Hu, Yong, Yu, Wenbin, Zhao, Feiyang
Journal Article
Variable Speed Limit Control Based on Deep Deterministic Policy Gradient under Mixed Traffic Environment12-09-01-000405/06/2025
The existing variable speed limit (VSL) control strategies rely on variable message signs, leading to slow response times and sensitivity to driver compliance. These methods struggle to adapt to environments where both connected automated vehicles (CAVs) and manual vehicles coexist. This article proposes a VSL control strategy using the deep deterministic policy gradient (DDPG) algorithm to optimize travel time, reduce collision risks, and minimize energy consumption. The algorithm leverages real-time traffic data and prior speed limits to generate new control actions. A reward function is designed within a DDPG-based actor-critic framework to determine optimal speed limits. The proposed strategy was tested in two scenarios and compared against no-control, rule-based control, and DDQN-based control methods. The simulation results indicate that the proposed control strategy outperforms existing approaches in terms of improving TTS (total time spent), enhancing the throughput efficiency
Ding, Xibin, Zhang, Zhaolei, Liu, Zhizhen, Tang, Feng
Journal Article
Research on NVH Performance of Pulse Heating System of One Vehicle2025-01-007805/05/2025
When the ambient temperature is too low, the performance of the lithium-ion battery will deteriorate, and the car will have the problems of difficult charging, fast power consumption, and even difficult to start, so the battery needs to be heated before use to provide a comfortable working environment for the lithium-ion. The high-frequency pulse heating system can quickly and evenly raise the temperature of the battery, but there is noise during operation, which affects the NVH performance of the vehicle itself, and its noise comfort needs to be further optimized. Firstly, the high-frequency pulse heating system is discussed in detail, and the parameters affecting the NVH performance are explored. Secondly, NVH tests and subjective and objective evaluations were carried out based on different system parameters, relevant data were collected to establish a model, the influence degree of each parameter was demonstrated, and the best parameter combination was determined. Finally, the
Yun, Zhao, Shouhui, Huang, Hu, Zhongxun, Hui, Hui, Zhou, Changshui, Teng, Charlie
Technical Paper
A Concept for Functional Modelling of an E-Bike Powertrain2024-32-001704/18/2025
The increasing popularity of e-bikes, especially pedelecs, has led to a growing interest in consideration of e-bike cycling. To achieve a deeper understanding on the process of e-bike cycling and in particular the effects on the rider it can be instrumental to use simulation methods. In this context, the e-bike drive system and its function are of central importance for e-bikes. Therefore, this work proposes a functional modeling of the powertrain of an e-bike with a mid-drive motor, considering legal constraints and support functionalities. The model incorporates the mechanical transmission between pedals, motor, and crank shaft, allowing for a detailed analysis of the e-bike’s performance. Additionally, the support mechanism is depicted, where an electric motor amplifies the rider’s pedaling torque. The electrical behavior of the motor, energy consumption, and battery state of charge are also integrated into the model. This comprehensive approach aims to provide a generic
Rauch, Yannick, Kettner, Maurice, Kriesten, Reiner
Technical Paper
Experiment Characterization and Simulation Analysis of a Lithium-Ion Battery in Different Ambient Conditions2025-01-502804/15/2025
A great number of performances of an electric vehicle such as driving range, powering performance, and the like are affected by its configured batteries. Having a good grasp of the electrical and thermal behavior of the battery before the detailed design stage is indispensable. This paper introduces an experiment characterization method of a lithium-ion battery with a coolant system from cell level to pack level in different ambient conditions. Corresponding cell and pack simulation models established in AMESim that aimed to capture the electrical and thermal features of the battery were also illustrated, respectively. First, the capacity test and hybrid pulse power characterization (HPPC) test were conducted in a thermotank to acquire basic data about the battery cell. Next, based on acquired data, first-order equivalent circuit model (1C-ECM) was built for the battery cell and further combined with environmental boundary conditions to check the simulation accuracy. Then, hybrid
Zhou, Shuai, Liu, Huaiju, Yu, Huili, Yan, Xu, Yan, Junjie
Technical Paper
Predictive Battery Thermal Management System Control Strategy and Simulation in Electric Vehicle2025-01-502704/03/2025
With the global issue of fossil fuel scarcity and the greenhouse effect, interest in electric vehicles (EVs) has surged recently. At that stage, because of the constraints of the energy density and battery performance degradation in low-temperature conditions, the mileage of EVs has been criticized. To guarantee battery performance, a battery thermal management system (BTMS) is applied to ensure battery operates in a suitable temperature range. Currently, in the industry, a settled temperature interval is set as criteria of positive thermal management activation, which is robust but leads to energy waste. BTMS has a kilowatt-level power usage under high- and low-temperature environments. Optimizing the BTMS control strategy becomes a potential solution to reduce energy consumption and overcome mileage issues. An appropriate system simulation model provides an effective tool to evaluate different BTMS control strategies. In this study, a predictive BTMS control strategy, which adjusts
Huang, Zhipei, Chen, Jiangbo, Tang, Hai
Technical Paper
Learning-Based Energy Management Strategy of Fuel Cell City Buses Considering Power Source Degradation02-18-02-001204/02/2025
Fuel cell vehicles (FCVs) offer a promising solution for achieving environmentally friendly transportation and improving fuel economy. The energy management strategy (EMS), as a critical technology for FCVs, faces significant challenges of achieving a balanced coordination among the fuel economy, power battery life, and durability of fuel cell across diverse environments. To address these challenges, a learning-based EMS for fuel cell city buses considering power source degradation is proposed. First, a fuel cell degradation model and a power battery aging model from the literature are presented. Then, based on the deep Q-network (DQN), four factors are incorporated into the reward function, including comprehensive hydrogen consumption, fuel cell performance degradation, power battery life degradation, and battery state of charge deviation. The simulation results show that compared to the dynamic programming–based EMS (DP-EMS), the proposed EMS improves the fuel cell durability while
Song, Dafeng, Yan, Jinxing, Zeng, Xiaohua, Zhang, Yunhe
Journal Article
European Initiatives for User-Centric Design of Electric Vehicles2025-01-880704/01/2025
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 driving range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under
Ratz, Florian, Bäuml, Thomas, Kompara, Tomaž, Kospach, Alexander, Simic, Dragan, Jan, Petra, Möller, Sebastian, Fuse, Hiroyuki, Paredes Barros, Esteban, Armengaud, Eric, Amati, Nicola, Sorniotti, Aldo, Lukesch, Walter
Technical Paper
Systematic Predictive Energy Management Algorithm Testing in MIL/SIL with Realistic Traffic Simulation2025-01-858304/01/2025
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 a partial replacement to, and overcome the limitations of, vehicle testing. In the testing setup, random traffic generated by MATLAB® based on real-time traffic condition will be taken
Yan, Yue, Ma, Xiudan, Wei, Xinli, Xiong, Jie, Deng, Yunfei, Bradfield, Donald Edward
Technical Paper
A 3-D CFD Performance Simulation of a Feedback Controlled Variable Displacement Vane Pump2025-01-817904/01/2025
Variable Displacement Vane Pumps (VDVPs) are widely used in lubrication systems for engines, transmissions, and electric drive units. This study presents a Computational Fluid Dynamics (CFD) analysis of a rotational VDVP, coupled with an Oil Control Valve (OCV), to establish a feedback loop that regulates the eccentricity of the cam ring, and consequently, the pump’s outlet flow rate. In previous studies, Simerics-MP+ has been successfully utilized to model the VDVP without considering the OCV’s effect. The OCV consists of a solenoid valve coupled with a spring-loaded spool valve. Due to the absence of the actual valve geometry, the valve behavior in the CFD model is represented by a 2-D table that correlates the control chamber flow rate with both the supply and control pressures. The eccentricity of the cam ring is determined through an iterative process, balancing fluid torques from the vane chamber pressures and control chamber pressure, along with the spring torque. Simulation
Khatri, Rachit Rajesh, Liu, Yuchan, Pasunurthi, Shyam Sundar, Ahmed, Rayhan, Stallmann, John, Yang, Bo, Huang, Yuli, Sivaji, Rangarajan, Scheffler, David
Technical Paper
Smart Boosting: A Control Strategy for Optimized Energy Management with Boost Converter in Hybrid Electric Vehicles2025-01-858004/01/2025
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, Huo, Shichao, Sullivan, Claire, Berger, Daniel, Tischendorf, Christoph
Technical Paper
Energy Price Sensitivity and Cost Analysis of Battery Electric and Fuel Cell Powertrains for Class 8 Heavy-Duty Trucks in Real-World Scenarios: A 2024, 2035, and 2050 Perspective2025-01-859204/01/2025
This study evaluates the performance of alternative powertrains for Class 8 heavy-duty trucks under various 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 2024, 2035, and 2050, considering anticipated technological advancements. The analysis employed simulation models that accurately reflect vehicle dynamics, powertrain components, and energy storage systems, leveraging real-world driving data. An integrated simulation workflow was implemented using Argonne National Laboratory's POLARIS, SVTrip, Autonomie, and TechScape software. Additionally, a sensitivity analysis was performed to assess how fluctuations in energy and fuel costs impact the cost-effectiveness of various powertrain options. By 2035, battery electric trucks (BEVs) demonstrate strong cost competitiveness in the 0-250 mile and 250-500 mile ranges, especially when
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
Technical Paper
Comprehensive Gear Shift Schedule of Heavy-Duty Commercial Electric Trucks Based on Dual Axle Driving2025-01-851004/01/2025
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 dynamic and economy performance of the whole vehicle, as well as the gear distribution characteristics in the vehicle operation, a comprehensive shifting schedule 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 economics 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 0-100 km/h acceleration capability and specific energy consumption as the
Guo, Jun, Zhang, Yunqing, Wu, Jinglai
Technical Paper
An Investigation of the Inter-Vehicle Distances and Lateral Offsets on Aerodynamic Forces and Wake Structures of Vehicles Platooning2025-01-876904/01/2025
In traffic scenarios, the spacing between vehicles plays a key 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 vehicles
Mosavati, Maziar, Guzman, Arturo, Lounsberry, Todd, Fadler, Gregory
Technical Paper
On-Road Investigation of Energy Saving Opportunity for Autonomous Light-Duty Vehicles through Automated Vehicle-Following in Safe Distance Scenarios2025-01-802904/01/2025
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 investigation aimed at assessing energy reduction in 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 conducted 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 two sets of L4 capable light duty vehicles, including the Stellantis Pacifica PHEV minivan and Stellantis RAM Truck, examined in various lead and following vehicle
Poovalappil, Aman, Robare, Andrew, Schexnaydre, Logan, Santhosh, Pruthwiraj, Bahramgiri, Mojtaba, Bos, Jeremy P., Chen, Bo, Naber, Jeffrey, Robinette, Darrell
Technical Paper
Activity and Performance of Zero and Near-Zero Emissions Port Equipment for Emissions Reduction in the Maritime Sector2025-01-853904/01/2025
Marine ports are an important source of emissions in many urban areas, and many ports are implementing plans to reduce emissions and greenhouse gases using zero-emission cargo handling equipment. This paper evaluates the performance and activity profiles for various zero-emission (ZE) cargo transport equipment being demonstrated at different ports in California. This included 23 battery-electric (BE) 8,000 lb. (8K) and 36,000 lb. (36K) forklifts, a BE railcar mover, and an electrified rubber-tired gantry crane (eRTG). The study focused on evaluating the performance of the ZE equipment in terms of activity patterns and the potential emissions reductions. Data loggers were used to collect activity data, including hours of use, energy consumption, and charging information over periods from 6 to 21 months. The results showed that the BE forklifts, BE railcar mover, and the eRTG averaged 2-3 hours, 5 hours, and 14 hours of use per day of operation, respectively. The average energy use for
Frederickson, Chas, Vu, Alexander, Makki, Maedeh, Johnson, Kent, Durbin, Thomas, Burnette, Andrew, Huang, Eddy, Alvarado, Erica, Rao, Leela
Technical Paper
Evaluation of Different Powertrain Topologies for a Premium Plug-in Hybrid Electric Vehicle2025-01-853104/01/2025
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
Technical Paper
Energy Consumption Optimization of Commercial Electric Bus in Indian City Driving Condition Using Two Speed Transmission2025-01-850404/01/2025
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. Right now, most of the OEMs are using single speed transmission in their electric buses. Single speed transmission is effective in road having average speed around 20 to 25 kmph but during heavy traffic road condition (like Mumbai city application), average speed of vehicle comes down to 10 kmph. 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 we have to increase driving range, we have to optimize the energy consumption. We can address the issue of higher energy consumption in heavy traffic condition by using two speed transmission. With use of two speed
Saurabh, Saurabh, Amancharla, Naga Chaithanya, Bhardwaj, Rohit, Gadve, Dhananjay
Technical Paper
Leveraging Traffic-in-the-Loop Simulations to Assess the Impact of Traffic on Vehicle Energy Consumption2025-01-805404/01/2025
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 qualitatively assess how varying traffic conditions
Grano, Elia, Villani, Manfredi, Ahmed, Qadeer, Carello, Massimiliana
Technical Paper
Modeling and Simulation Analysis of an Electric Vehicle in Normal and Hot Ambient Conditions: Energy Consumption and Driving Range2025-01-815104/01/2025
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 multi-discipline 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°C and 38°C ambient conditions
Zhou, Shuai, Liu, Huaiju, Yu, Huili, Yan, Xu, Yan, Junjie
Technical Paper
The Impact of GCI Engines on Long-haul Trucks in the US and China2025-01-839604/01/2025
This study evaluates the impacts of the gasoline compression ignition (GCI) engine on heavy duty long-haul trucks in both the Chinese and US markets. The study examines various aspects such as vehicle performance requirements, fuel consumption, emissions, and ownerships costs, and how they influence the implementation and impact of new technologies in these markets. By considering a wide variety of drive cycles, including standard regulatory cycles and real-world cycles, the study aims to identify the impact of varying degrees of powertrain electrification using diesel and GCI engines on fuel consumption and emissions. Additionally, this paper explores the viability of powertrain electrification in long-haul trucks by analyzing factors such as levelized cost of driving (LCOD), manufacturing costs, and energy costs. These considerations play a crucial role in determining the economic feasibility and attractiveness of electrification technologies in various driving scenarios and market
Nieto Prada, Daniela, Vijayagopal, Ram, Yan, Ziming, Sari, Rafael, He, Xin
Technical Paper
Robust V2X Cruise Control for Class 8 Trucks in the Presence of Traffic Lights2025-01-803304/01/2025
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 when possible while 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 in the higher level MPC
Ellison, Evan, Ward, Jacob, Brown, Lowell, Bevly, David M.
Technical Paper
Coupled Routing and Charge Schedule Optimization of Electrified Delivery Truck Fleets: Feasibility Analyses2025-01-860204/01/2025
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 coupled routing and charge scheduling optimization of a delivery fleet serving a large urban area as one approach to discovering feasible pathways. To this end, we first build an improved energy consumption model for a Class 7-8 electric and diesel truck using a data-driven approach of generating energy consumption data from detailed powertrain simulations on numerous drive cycles. We then conduct several analyses on the impact of battery pack capacity, cost, and electricity prices on the amortized daily total cost of fleet electrification at different penetration levels, considering availability of fast
Wendimagegnehu, Yared Tadesse, Ayalew, Beshah, Ivanco, Andrej, Hailemichael, Habtamu
Technical Paper
Digital Twin, A Multiphysics Numerical Tool Chain for Next Generation Electric Drive Design2025-01-862404/01/2025
Following early adoption, the BEV market has shifted towards a mass market strategy, emphasizing on crucial attributes, such as system cost reduction and range extension. System efficiency is crucial in BEV product development, where efficiency metric influenced greatly vehicle range and cost. For instance, higher iDM efficiency reduces the need for larger battery, cutting cost, or extends range with the same battery size. BorgWarner adopted Digital Twin technology to optimize Integrated Drive Module (iDM) within a vehicle ecosystem. Digital Twin comprises high-fidelity physics based numerical tool suites offering greater degree of freedom to engineers in designing, sizing, optimizing a component versus system benefit tradeoff, thus enabling most efficient product design within economic constraints. BorgWarner’s Analytical System Development (ASD) plan used as framework provides a global unified process for tool development and validation, ensuring the digital print of a real product
Bossi, Adrien, Bourniche, Eric, Leblay, Arnaud, David, Pascal, Nanjundaswamy, Harsha
Technical Paper
On-Vehicle Optimum Route Selection for a Plug-In Hybrid Electric Vehicle2025-01-838804/01/2025
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 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 vehicle used in this investigation is the Stellantis Pacifica PHEV. 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
Technical Paper
Assessing the Energy Consumption Impact of Intelligent Driving Technologies on Electric Vehicles: A Comprehensive Review2025-01-859804/01/2025
With the continuous advancement of artificial intelligence technology, the automation level of electric vehicles (EVs) is rapidly increasing. Despite the improvements in travel efficiency, safety, and convenience brought about by automation, cutting-edge intelligent technologies also pose the potential of increased energy consumption, such as the computational power required by advanced algorithms and the energy usage of high-precision equipment, leading to higher overall energy consumption for connected or autonomous electric vehicles (CAEVs). To assess the impact of intelligent technologies on AEVs, this study innovatively provides a comprehensive evaluation of the impact of intelligent technologies on CAEV energy consumption from both positive and negative perspectives. After reviewing 59 relevant studies, the findings highlight energy savings achieved through Vehicle-to-Infrastructure and Vehicle-to-Vehicle cooperation as positive effects, while increased energy consumption from
Liu, Tianyi, Qi, Hao, Ou, Shiqi (Shawn)
Technical Paper
An Integrated Data-Driven and Physics-Based Approach for Dynamic Operation Simulation of Electric Vehicles2025-01-860404/01/2025
To address the challenges of complex operational simulation for Electric Vehicles (EVs) caused by spatial-temporal variations and driver behavior heterogeneity, this study introduces a dynamic operation simulation model that integrates both data-driven and physics-based principles, referred to as the Electric Vehicle-Dynamic Operation Simulation (EV-DOS) model. The physics-based component encompasses critical aspects such as the powertrain energy transfer module, heat transfer module, charge/discharge module, and battery state estimation module. The data-driven component derives key features and labels from second-by-second real-world vehicle driving status data and incorporates a Long Short-Term Memory (LSTM) network to develop a State-of-Health (SOH) prediction model for the EV power pack. This model framework combines the interpretability of physical modeling with the rapid simulation capabilities of data-driven techniques under dynamic operating conditions. Finally, this study
Jing, Hao, HU, Jianyao, Ouyang, Jianheng, Ou, Shiqi(Shawn)
Technical Paper
Simulation of GHG Emissions for Production Phase of Battery Electric and Hydrogen Fuel Cell Electric HDVs under Different Electricity Grid Mixes2025-01-859904/01/2025
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 emissions heavy-duty trucks is facing enormous technical and economic challenges. This work investigated GHG emissions during the manufacturing and assembly phase of heavy-duty vehicles (HDVs), including battery electric trucks (BETs) and gaseous hydrogen fuel cell electric trucks (FCETs) using SimaPro software package with wildly accepted Ecoinvent database based on UK grid mix scenarios. A comparative analysis of greenhouse gas (GHG) emissions during the production phase of 700 bar- and 350 bar-H2 FCETs and their battery electric counterparts (eqBETs) was conducted under two UK
Zhao, Jianbo, Li, Hu, Babaie, Meisam, Li, Kang
Technical Paper
Fully Automated Global Powertrain Optimization for Electric Truck Using Active Learning Algorithm and Backwards Simulation Approach2025-01-853604/01/2025
Electric trucks, due to their weight and payload, need a different layout than passenger electric vehicles (EVs). They require multiple motors or multi-speed transmissions, unlike passenger EVs that often use one motor or a single-speed transmission. This involves determining motor size, number of motors, gears, and gear ratios, complicated by the powertrain system’s nonlinearity. The paper proposes using a stochastic active learning approach (Bayesian optimization) to configure the motors and transmissions for optimal efficiency and performance. Backwards simulation is applied to determine the energy consumption and performance of the vehicle for a rapid simulation of different powertrain configurations. Bayesian optimization, was used to select the electric drive unit (EDU) design candidates for two driving scenarios, combined with a local optimization (dynamic programming) for torque split. By optimizing the electric motor and transmission gears, it is possible to reduce energy
Chen, Bicheng, Wellmann, Christoph, Xia, Feihong, Savelsberg, Rene, Andert, Jakob, Pischinger, Stefan
Technical Paper
Development of the Power- and Usage-Based Simulator for Evaluating Off-Road Mobile Machinery Energy Consumption2025-01-859504/01/2025
This paper presents the development of a new vehicle simulation software, the Power- and Usage-Based Simulator Tool (referred to as the Power-Based Model), designed to predict fuel consumption and evaluate advanced powertrain technologies for off-road mobile machinery. The Power-Based Model integrates current research on fuel consumption simulation in the off-road vehicle sector and serves as a platform for development of advanced powertrain technologies such as battery-electric and fuel cell powertrains. The tool predicts the battery capacity and hydrogen storage required for the transition to these advanced powertrains, allowing users to accurately calculate component sizes and reductions in fuel consumption. The Power-Based Model was developed with a strong focus on the unique operational characteristics of off-road machinery, ensuring that it realistically reflects real-world energy consumption and the competitive advantages of various fuel-saving technologies. This paper describes
Kim, Namdoo, Seo, Jigu, Vijayagopal, Ram, Burnham, Andrew, makarczyk, David, Freyermuth, Vincent
Technical Paper
Electro-Thermal Optimal Control for Driver-Centric DC Fast Charging of Electric Vehicles2025-01-837404/01/2025
Charging a battery electric vehicle at extreme temperatures can lead to battery deterioration without proper thermal management. To avoid battery degradation, charging current is generally limited at extreme hot and cold battery temperatures. Splitting the wall power between charging and the thermal management system with the aim of minimizing charging time is a challenging problem especially with the strong thermal coupling with the charging current. Existing research focus on formulating the battery thermal management control problem as a minimum charging time optimal control problem. Such control strategy force the driver to charge with minimum time and higher charging cost irrespective of their driving schedule. This paper presents a driver-centric DCFC control framework by formulating the power split between thermal management and charging as an optimal control problem with the goal of improving the wall-to-vehicle energy efficiency. Proposed energy-efficient charging strategy
Gupta, Shobhit, Kang, Jun-Mo, Zhu, Yongjie, Lee, Chunhao, Zanardelli, Wesley
Technical Paper
Energy Savings and Range Extension from Aerodynamic Improvements of Emerging Zero-Emission Heavy Vehicle Concepts2025-01-878704/01/2025
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 commercial vehicles 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 modern 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 energy use, and potential savings thereof, from implementing various fleet configurations for different operational duty cycles. An energy-use analysis was implemented to estimate the energy-rate contributions associated
McAuliffe, Brian, Ghorbanishohrat, Faegheh
Technical Paper
Reducing Power Consumption through Effective Data Sharing in Platooning Scenarios2025-01-805104/01/2025
Platooning occurs when vehicles travel closely together to benefit from multi-vehicle movement, increased road capacity, and reduced fuel consumption. This study focused on reducing energy consumption under different driving scenarios and road conditions. To quantify the energy consumption, we first consider dynamic events that can affect driving, such as braking and sudden acceleration. In our experiments, we focused on modeling and analyzing the power consumption of autonomous platoons in a simulated environment, the main goal of which was to develop a clear understanding of the different driving and road factors influencing power consumption and to highlight key parameters. The key elements that influence the energy consumption can be identified by simulating multiple driving scenarios under different road conditions. The initial findings from the simulations suggest that by efficiently utilizing the inter-vehicle distances and keeping the vehicle movements concurrent, the power
Khalid, Muhammad Zaeem, Azim, Akramul, Rahman, Taufiq
Technical Paper
Enhancement in Cabin Comfort and Overall Energy Utilization of an Electric Reverse Trike Car by Optimizing the System Layout2025-01-815004/01/2025
The rapid adoption of electric vehicles (EVs), driven by stricter emissions norms, is transforming both urban and rural mobility. However, significant challenges remain, particularly concerning the charging infrastructure and battery technology. The limited availability of charging stations and the reliance on current high-energy-density cells restrict the overall effectiveness of the e-mobility ecosystem. These constraints lead to shorter vehicle ranges and longer charging times, contributing to range anxiety—one of the most critical barriers to widespread EV adoption. Adding to these challenges, auxiliary systems, especially air-conditioning (AC) systems, significantly impact energy consumption. Among all auxiliary systems, the AC system is the most energy-intensive, often exacerbating range anxiety by reducing the distance an EV can travel on a single charge. Hence, it is essential to focus on enhancing the efficiency of AC systems. This involves redefining and optimizing system
Sen, Somnath, Jadhav, Yash, Singh, Karamjeet, Sorte, Swapnil, Anwar, Md Tahir
Technical Paper
A Novel Co-Simulation Framework for Optimizing Human Thermal Comfort and Energy Consumption in a Vehicle2025-01-819104/01/2025
A major portion of the energy consumed in a vehicle is spent on keeping the occupants thermally comfortable in all environmental conditions when the heating, ventilation, and air-conditioning (HVAC) system is turned on. Maintaining the thermal comfort of a passenger is critical in terms of fuel consumption and emission for internal combustion engine (ICE) vehicles. In electrified vehicles, where range is of major concern, this gains further-more importance. SC03 is a test defined by the US Environmental Protection Agency (EPA) to measure tailpipe emissions and fuel economy of passenger cars with the air-conditioner on. The current study would focus on this drive cycle on an ICE vehicle. The co-simulation framework would include a 1D thermal system model, associated thermal controls, a vehicle cabin model, and a human thermal model. 1D model will be predicting the energy consumption via compressor power, refrigerant pressure and temperature across the loop, component heat rejection, etc
Natarajan, Shankar, Balasubramanian, Sudharsan
Technical Paper
Portable Track-Based Connected Intersection Testing System for Connected and Automated Vehicles2025-01-806204/01/2025
Connected and automated vehicle (CAV) technology is a rapidly growing area of research as more automakers strive towards safer and greener roads through its adoption. The addition of sensor suites and vehicle-to-everything (V2X) connectivity gives CAVs an edge on predicting lead vehicle and connected intersection states, allowing them to adjust trajectory and make more fuel-efficient decisions. Optimizing the energy consumption of longitudinal control strategies is a key area of research in the CAV field as a mechanism to reduce the overall energy consumption of vehicles on the road. One such CAV feature is autonomous intersection navigation (AIN) with eco-approach and departure through signalized intersections using vehicle-to-infrastructure (V2I) connectivity. Much existing work on AIN has been tested using model-in-loop (MIL) simulation due to being safer and more accessible than on-vehicle options. To fully validate the functionality and performance of the feature, additional
Hamilton, Kayla, Misra, Priyashraba, Ord, David, Goberville, Nick, Crain, Trevor, Marwadi, Shreekant
Technical Paper
Modular Dynamometer Testing Framework to Evaluate Energy Impacts of Longitudinal Automated Driving Systems2025-01-806504/01/2025
As longitudinal Automated Driving System (ADS) technologies, such as Adaptive Cruise Control (ACC), become more prevalent, robust testing frameworks that encompass both simulation and vehicle-in-the-loop (VIL) methodologies are essential to ensure system reliability, safety, and performance refinement. Although significant research has focused on ACC algorithm development and simulation testing, existing VIL dynamometer testing frameworks are typically tailored to specific vehicle models and sensor simulation tools. These highly customized approaches often fail to account for broader interoperability while overlooking energy consumption as a key performance metric. This paper presents a novel modular framework for ACC dynamometer testing, designed to enhance interoperability across a diverse range of vehicle platforms, simulation tools, and dynamometer facilities with a focus on evaluating impacts of automated longitudinal control on the overall energy consumption of the vehicle. The
Goberville, Nicholas, Hamilton, Kayla, Di Russo, Miriam, Jeong, Jongryeol, Das, Debashis, Ord, David, Misra, Priyashraba, Crain, Trevor
Technical Paper
Machine Learning-Based Digital Twin for Optimizing Automotive Components2025-01-820604/01/2025
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 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 lifecycle. The
Khan, Jalal, D'Alessandro, Stefano, Tramaglia, Federico, Fauda, Alessandro
Technical Paper
Optimizing Battery Charging Strategies through Q-Learning and Electric Vehicle Powertrain System Modeling2025-01-811604/01/2025
Battery health status and driving rangeof electric vehicles (EVs) are critical factors in determining their market penetration. Choosing an optimal charging strategy—specifying how, when, and for how long to charge based on the driver’s travel behavior—can significantly mitigate battery degradation and extend battery life. This study introduces an EV powertrain system energy model designed to enhance the prediction accuracy of battery status under real-world driving conditions. By integrating with the Q-learning approach, this studyprovides tailored recommendations on charging behaviors, including charger type, start time, and charging duration. This study innovatively considers the rental costs caused by the battery capacity not being able to meet the daily driving range. Simulating a typical three-year usage scenario for an average driver in New England, the results indicate that thecharging strategy proposed by this study reduces battery degradation rates by 1.53‰, 3.57‰, and 7.68
Wang, Jiayi, Jing, Hao, Ou, Shiqi (Shawn), Lin, Zhenhong
Technical Paper
Modeling and Simulation Analysis of an Electric Vehicle in Cold Ambient Conditions: Energy Consumption and Impact of Battery Heating on Driving Range2025-01-814204/01/2025
Thanks to greatly increased energy density of battery, the average driving range of an electric vehicle has been advanced quite a lot. However, drastic reduction of driving range in cold ambient conditions still greatly restricts the wide application of electric vehicles. This paper presents a methodology of establishing multi-discipline coupled full vehicle model in AMESim to investigate the energy consumption of a pure electric vehicle in cold ambient conditions. Different strategies of battery heating through Positive Temperature Coefficient (PTC) part and/or combination of Motor Waste Heat Recovery (MWHR) were also investigated to study whether there is an improvement of driving range. Firstly, basic framework of the full vehicle model established in AMESim was introduced. Next, modeling details of individual sub-systems were illustrated respectively. Then, full vehicle energy consumption test was carried out in -7°C ambient condition to check the simulation accuracy. Finally, a
Zhou, Shuai, Liu, Huaiju, YU, Huili, Yan, Xu, Yan, Junjie
Technical Paper
Control Trajectory Optimization of Electric Vehicle Heat Pump-Based Cabin Heating System2025-01-814404/01/2025
Optimal control of battery electric vehicle thermal management systems is essential for maximizi ng the driving range in extreme weather conditions. Vehicles equipped with advanced heating, ventilation and air-conditioning (HVAC) systems based on heat pumps with secondary coolant loops are more challenging to control due to actuator redundancy and increased thermal inertia. This paper presents the dynamic programming (DP)-based offline control trajectory optimization of heat pump-based HVAC aimed at maximizing thermal comfort and energy efficiency. Besides deriving benchmark results, the goal of trajectory optimization is to gain insights for practical hierarchical control strategy modifications to further improve real-time controllers’ performance. DP optimizes cabin inlet air temperature and flow rate to set the trade-off between thermal comfort and energy efficiency while considering the nonlinear dynamics and operating limits of HVAC system in addition to typically considered cabin
Cvok, Ivan, Deur, Josko
Technical Paper
Research on Motor Harmonic Injection Control in Hybrid System to Suppress the Torsional Vibration2025-01-851504/01/2025
Based on the harmonic current injection method used to suppress the torsional vibration of the electric drive system, the selection of the phase and amplitude of the harmonic current based on vibration and noise has been explored in this paper. Through the adoption of the active harmonic current injection method, additional torque fluctuations are generated by actively injecting harmonic currents of specific amplitudes and phases, and closed-loop control is carried out to counteract the torque fluctuations of the motor body. The selection of the magnitude of the injected harmonic current is crucial and plays a vital role in the reduction of torque ripple. Incorrect harmonic currents may not achieve the optimal torque ripple suppression effect or even increase the motor torque ripple. Since the actively injected harmonic current is used to counteract the torque ripple caused by the magnetic flux linkage harmonics of the motor body, the target harmonic current command is very important
Jing, Junchao, Zhang, Junzhi, Liu, Yiqiang, Huang, Weishan, Dai, Zhengxing
Technical Paper
Impact of Hybrid Electric Vehicles on Energy Consumption and Emission Reduction for Agricultural Applications2025-01-854004/01/2025
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 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 electric power and mechanical power, enabling intelligent management
Prasad, Lakshmi P., PS, Satyanarayana, Paygude, Tejas, Gangsar, Purushottam, Thakre, Mangesh, Choudhary, Nagesh, Gitapathi, Ajinkya
Technical Paper
Demonstration of Model Predictive Control to Optimise Cabin Thermal Comfort in a Battery Electric Vehicle2025-01-814504/01/2025
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
Technical Paper
Comparative Analysis of Mass Estimation Methods for Heavy-Duty Vehicles under Varying Payload Conditions2025-01-820904/01/2025
Accurate mass estimation is essential for commercial heavy-duty vehicles (HDVs) because 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. For electric HDVs, accurate mass estimates are crucial for battery sizing, range prediction, and optimized charge scheduling. 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 systems for alternative real-time predictions. The challenge lies in identifying a method that performs well under the highly variable and often sparse data conditions typical of HDV driving datasets
Jayaprakash, Bharat, Eagon, Matthew, Fakhimi, Setayesh, Kotz, Andrew, Northrop, William
Technical Paper
On the Potentially Misleading Evaluation of CO 2 Emissions for Hybrid-Electric Vehicles2025-01-853704/01/2025
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
Technical Paper
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