Browse Topic: Energy management

Items (2,937)

Model-Based Design and Energy Management of an Aeronautical Proton Exchange Membrane Fuel Cell System

2025-01-0150To be published on 04/25/2025

The growing demand for air transport requires efficient and sustainable power systems to meet the pressing need for decarbonizing the sector. A hybrid unit, consisting of a proton exchange membrane fuel cell system and a lithium-ion battery, is a suitable option due to the benefits of reduced gravimetric and volumetric impacts, along with the flexibility of energy management strategies. This work addresses, using a model-based approach, the issue of integrating these electrochemical devices into the aircraft’s electrical architecture, considering both design and energy management aspects. Two scenarios are explored to match the DC bus line voltage requirements. In the first, the fuel cell system nominal power is kept constant, while the number of DC/DC converters operating in parallel is assessed by constructing bi-dimensional maps derived from literature. These maps relate the converter’s maximum deliverable power to the input and desired output voltage. The second scenario introduces

Aliberti, Paolo, Sorrentino, Marco, Cuomo, Fabrizio, Napolitano, Ciro

Designing and Controlling a Hybrid Fuel Cell System for Propelling a Turboprop Aircraft

2025-01-0151To be published on 04/25/2025

In the context of aviation sector decarbonization, fuel cell hybrid electric aircrafts are a promising alternative to conventional fuels, presenting opportunities for more sustainable and efficient flight. Hence, the present work is focused on an alternative powertrain architecture, wherein a proton exchange membrane fuel cell system cooperates with a lithium-ion battery to fulfill the electrical power demand of a turboprop-based aircraft. Particularly, a mathematical tool is proposed to evaluate both the components size and performance, while a degradation aware rule-based control strategy guarantees an effective power split between the hybridizing components. Such an energy management approach introduces an idling level and a rate limiter to mitigate degradation associated with start-up/shut-down and transient phases, respectively. Moreover, to have a reliable estimation of the vehicle’s fuel economy, while also guaranteeing the correct components dimensioning, the fuel cell system

De Donato, Angelo, Aliberti, Paolo, Sorrentino, Marco, Cuomo, Fabrizio, Musto, Carmine

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

Enhancement in Cabin Comfort and Overall Energy Utilization of an Electric Reverse Trike Car by Optimizing the System Layout

2025-01-8150To be published on 04/01/2025

As the emissions norms are getting stringent and stricter, the use of all electric vehicles is widespread and becoming mainstream mobility both in urban and rural areas. However, lack of good charging infrastructure and high energy density cells limiting the overall electric mobility eco-system. Eventually the shorter range and high charging time of the vehicle is becoming the key challenge of e-mobility. Energy consumption by one of the key auxiliary systems e.g. air-conditioning (AC) system is adding further concerns over the range anxiety. It is the most energy consuming system among all others. Hence the need of the hour is to improve and enhance the AC system performance by means of redefining and optimizing the system layout in order to reduce power drawn by system. The present paper evaluates the improvement of cabin comfort and reduce the energy consumption of an electric car AC system by optimizing the layout and position of condenser and compressor. The experiments were

Sen, Somnath, Jadhav, Yash, Singh, Karamjeet, Sorte, Swapnil, Anwar, Md Tahir

Digital Twin, A Multiphysics Numerical Tool Chain for Next Generation Electric Drive Design

2025-01-8624To be published on 04/01/2025

Following an early adoption phase, the BEV market focus shift towards mass market strategy. This shift has placed greater emphasis on crucial attributes, such as system cost reduction and range extension. System efficiency has always been at the center of the BEV product development, where efficiency metric influenced greatly the range and cost of the vehicle. For example, higher efficiency of an iDM (Integrated Drive Module) reduces the need for bigger battery thus cost reduction, alternatively for a same battery size the end user will benefit with an extended range. BorgWarner adopted Digital Twin technology to optimize iDM within a vehicle ecosystem, Digital Twin is an assembly of high-fidelity physics based numerical tool suites which offer greater degree of freedom to engineers in designing, sizing, optimizing a component vs. system benefit tradeoff, thus enabling most efficient product design within constraints of economics. At BorgWarner we have adopted Analytical System

Bossi, Adrien, Bourniche, Eric, Leblay, Arnaud, David, Pascal, Nanjundaswamy, Harsha

Modular Dynamometer Testing Framework to Evaluate Energy Impacts of Longitudinal Automated Driving Systems

2025-01-8065To be published on 04/01/2025

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 impact 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

Reducing Power Consumption through Effective Data Sharing in Platooning Scenarios

2025-01-8051To be published on 04/01/2025

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

Systematic Design Considerations of Motor Selections for EV Powertrain

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

As one of the most important design choices in the powertrain design cycle, motor selection is conventionally performed according to given automotive requirements. Motor-related powertrain design parameters like gear ratio, power output ratio between different axles, are excluded from the motor design process. In this paper, three comparative studies are performed to investigate the impact of these motor-related powertrain design parameters on the motor performance and the weight/cost/efficiency of the entire EV powertrain. In the first study, three PM motor designs—characterized by high, medium, and low rated speeds—will be assessed for a two-axle EV using various gear ratio configurations. The same motor design will be used for both axles. In the second study, five motor designs with varying power and ratings (PM, non-PM) but identical rated speeds will be evaluated for a two-axle EV, permitting different power ratings for the front and rear axles. The design trade-offs between motor

Movahed, Ehsan, Godbehere, Jonathan, Jia, Yijiang

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

Development of the Power- and Usage-based Simulator for evaluating Off-road Mobile Machinery Energy Consumption

2025-01-8595To be published on 04/01/2025

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 to pilot the development of advanced powertrain technologies such as battery-electric and fuel cell powertrains. The tool is aimed at predicting the necessary battery capacity and hydrogen storage requirements when transitioning to these advanced powertrains, thereby facilitating component sizing and fuel consumption reduction calculations. 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

Kim, Namdoo, Seo, Jigu, Vijayagopal, Ram, Burnham, Andrew, makarczyk, David, Freyermuth, Vincent

Assessing the Energy Impact of Intelligent Driving Technologies on Electric Vehicle: A Comprehensive Review

2025-01-8598To be published on 04/01/2025

With the continuous development of artificial intelligence technology, the automation level of electric vehicles is rapidly advancing. However, while automation enhances travel efficiency, safety, and convenience, it also leads to increased energy consumption due to high-level intelligent driving technologies, resulting in higher overall energy consumption of intelligent electric vehicles compared to traditional vehicles. To assess the impact of autonomous driving systems on vehicle energy consumption, this study collected data on vehicle operating conditions and energy consumption under different levels of intelligence through literature review and expert consultations. The study analyzed both the positive and negative impacts of intelligent driving technologies on vehicle energy consumption at various levels of driving automation, including energy savings achieved by intelligent technologies through traffic signal control to reduce congestion, as well as the additional energy

Liu, Tianyi, Qi, Hao, Ou, Shiqi (Shawn)

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

Modeling and Simulation analysis of an electric vehicle in clod ambient conditions: energy consumption and impact of battery heating on driving range

2025-01-8142To be published on 04/01/2025

Thanks to greatly increased energy density of battery, the average driving range of electric vehicles have been advanced quite a lot. However, drastic reduction of driving range in cold ambient conditions still greatly restricts the wide application of it. This paper presents a methodology of establishing mechanics-electricity-thermodynamics 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℃ ambient condition to check the simulation accuracy. Finally, a

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

Portable Track-Based Connected Intersection Testing System for Connected and Automated Vehicles

2025-01-8062To be published on 04/01/2025

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 CAV enabled vehicles 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 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

Hamilton, Kayla, Misra, Priyashraba, Ord, David, Goberville, Nick, Crain, Trevor, Marwadi, Shreekant

Research on energy recovery strategy in breaking of electric tractor-semitrailer

2025-01-8290To be published on 04/01/2025

Tractor-semitrailers play an important role in the transportation industry. However, global warming and the rapid advancement of energy technologies have driven the transformation of high-emission vehicles, such as tractor-semitrailers, to be powered by new energy sources in order to achieve goals related to energy conservation, emission reduction, and cost savings. By using the motor as the primary driving force, the energy recovered during braking or coasting can be converted into electricity and stored in the battery for later use. While much research has been conducted on braking control and energy recovery for passenger cars, there is limited research on tractor-semitrailers. Additionally, the jackknife is a critical factor to consider under high-speed conditions. To investigate the braking energy recovery of electric tractor-semitrailers, tire and motor models were developed based on the turning and braking conditions of such vehicles. Taking into account the load transfer effect

Chen, Runping, Duan, Yupeng

Research on the Parameter Optimization Method for a Dual-Motor Coupled Integrated Single-Axle Drive System

2025-01-8284To be published on 04/01/2025

This paper explores a parameter optimization calculation method for a dual-motor coupled integrated single-axle drive system, aiming to achieve the optimal balance between vehicle dynamics, fuel efficiency, and system efficiency under this configuration. By constructing a vehicle longitudinal dynamics model and referencing motor models, the effective operating range is calculated. Vehicle acceleration time, gradeability, and maximum speed are used as constraints, while the proportion of the high-efficiency operating area of the drive system is taken as the objective function for optimizing relevant system parameters. This method improves computational efficiency by dividing the contour lines, thus eliminating the need to traverse all points in the constraint area and converting them into an intuitive analysis of the operating range, which reduces the need for point-by-point calculations across the entire working area.

Gu, Zhuangzhuang, You, Jianhui, Wu, Jinglai, Zhang, Yunqing

Control Trajectory Optimization of Electric Vehicle Heat Pump-based Cabin Heating System

2025-01-8144To be published on 04/01/2025

Optimal control of battery electric vehicle thermal management systems is essential for maximizing 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

Optimizing Charging Infrastructure and Schedules for Electrified Heavy-Duty Fleets: A Grid Resilience Approach

2025-01-8120To be published on 04/01/2025

Vehicle electrification, particularly for heavy-duty vehicles like school buses, offers substantial benefits, including energy savings, reduced greenhouse gas emissions, and improved student health outcomes. However, adopting electric heavy-duty vehicles presents additional challenges compared to conventional vehicles. Key issues include the high initial cost and recharging constraints, particularly the limitations of existing charging infrastructure. As a result, the fleet electrification of heavy-duty buses and logistic trucks often requires the development of dedicated depot charging infrastructure. Moreover, when constructing such infrastructure, it is essential to consider not only the installation and management costs but also grid resilience. This study addresses the requirements for charging infrastructure and plans charging strategies from a grid resilience perspective to support a sustainable electric vehicle fleet, using real operational data from school bus fleets. For this

Moon, Joon, Hanif, Athar, Ahmed, Qadeer

Optimization of Electric Vehicle Battery Charging Strategy Based on Reinforcement Learning

2025-01-8116To be published on 04/01/2025

The battery capacity of electric vehicles (EVs) is a critical factor influencing their overall performance. Selecting an appropriate charging strategy based on the EV driver’s travel behaviors can significantly mitigate battery capacity degradation and prolong its lifespan. This study integrated a physics-based battery degradation model with an EV powertrain system energy consumption model to enhance the prediction accuracy for the battery status under real-world driving conditions. In addition, it employed the Q-learning algorithm to provide suggestions on the driver’s charging behaviors, including charging start time, charging duration, and charger types. To create a reasonable reward function in the Q-learning algorithm, this study addressed the issue of car rental costs when the battery capacity is insufficient to support daily mileage. With the algorithm, this study modeled the 3-year use of an EV by an average driver sampled from the New England area in the U.S. The simulation

Wang, Jiayi, Jing, Hao, Ou, Shiqi (Shawn), Lin, Zhenhong

A Novel Co-Simulation Framework for Optimizing Human Thermal Comfort and Energy Consumption

2025-01-8191To be published on 04/01/2025

A major portion of the energy consumed in a vehicle is spent on keeping the occupants thermally comfortable in all environmental conditions. 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, blower power, etc. 1D-3D co-simulation approach is used for modeling the cabin. Berkeley human comfort model has been used in recent times to get a subjective

Natarajan, Shankar, Balasubramanian, Sudharsan

Modal Analysis Approach for Analysis and Design of Vehicle Transient Behavior

2025-01-8794To be published on 04/01/2025

In order to solve the increasingly serious global environmental problems, the automobile industry is rapidly shifting to EVs and plug-in hybrid EVs, so vehicle weights are increasing. In addition, the use of low rolling resistance tires to improve energy efficiency is increasing. In order to ensure the maneuverability and stability of such vehicles, it is becoming increasingly necessary to design performance based on better understanding of the basic principles of vehicle dynamics. Vehicle dynamics is fundamentallilly based on planar motion, but the accompanying roll motion also affects the planar motion and also driver's subjective evaluation. Vehicle dynamics analysis considering roll has been discussed by parameter studies, by characteristic analysis using equivalent models, or by characteristic root analysis. However, with the exception of R.S Sharp's report, which mentions the three vibration modes of motorcycles, there are very few examples of vehicle dynamics analysis in terms

Kusaka, Kaoru, Yuhara, Takahiro

Driver-Centric Direct Current Fast Charging of Electric Vehicles via Energy Optimal Thermal Management

2025-01-8374To be published on 04/01/2025

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. The current control strategy forces 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

Gupta, Shobhit, Kang, Jun-Mo, Zhu, Yongjie, Lee, Chunhao, Zanardelli, Wesley

Power Loss Estimation in Poly-V Belts for Micro and Mild Hybrid Powertrains Using the Generalized Maxwell Model

2025-01-8316To be published on 04/01/2025

In modern automotive powertrains, the front-end accessory drive represents a crucial subsystem that guarantees the proper functioning of micro and mild hybrid configurations and auxiliary vehicle functionalities. The motor/generator (12 V or 48 V), the air conditioning compressor and other accessories rely on this subsystem. Therein, the poly-V belt is the main transmission mechanism. From an efficiency standpoint, its behavior is usually represented through slip and elastic shear phenomena. However, the viscoelastic nature of the compounds that constitute the belt layers demand a more detailed approximation of the loss mechanisms. The quantification of such losses allows evaluating the performance of the e-machine integrated in the powertrain and improving its control. This work models the belt through a lumped-parameter time-domain model, where domains are discretized into multiple elements and represented through the generalized Maxwell model. Loss contributions due to bending

Galluzzi, Renato, Amati, Nicola, Bonfitto, Angelo, Hegde, Shailesh, Zenerino, Enrico, Pennazza, Mario, Staniscia, Emiliano

Development of the New 2.0L In-Line 4 NA Gasoline Direct Injenction Engine

2025-01-8395To be published on 04/01/2025

In recent years, from the viewpoint of climate change prevention and environmental protection, fuel efficiency and exhaust gas regulations in each country have become increasingly stringent year by year.　The share of electric vehicle and hybrid vehicle are expanding, especially in developed countries.　However, the sales ratio of gasoline vehicle is still high in the global automobile market. Therefore, it is very important to improve the environmental performance of gasoline engines from the viewpoint of environmental protection on a global scale.　Then, Honda has developed a new engine for gasoline vehicles with enhanced fuel economy and emissions performance. The newly developed gasoline engine makes maximum use of the structure and components of a gasoline engine for hybrid vehicles with excellent environmental performance that was developed in advance. As a result, in a short development period, the newly developed gasoline engine realized high environmental performance with low

Kondo, Takashi, Ohmori, Takeyuki, Yamamoto, Junpei, Miki, Kentaro

10 % Fuel Economy Benefit at Part Load and up to 33 % at idle for a Diesel Engine via Reducing Friction. Testing the Rotating Liner Engine and an Identical Baseline Under Load

2025-01-8390To be published on 04/01/2025

The Rotating Liner Engine (RLE) is a design concept where the cylinder liner of a heavy-duty Diesel engine rotates at about 2-4 m/s surface speed to eliminate the piston ring and skirt boundary friction near the top and bottom dead center. Two single cylinder engines are prepared using the Cummins 4BT 3.9 platform, one is RLE, the other is baseline (BS), i.e. conventional. published the test results of the RLE under load, but we lacked detail test data for the baseline. In this new set of experiments, we compare the RLE performance at idle and under load of up to about 7 bar IMEP (indicated mean effective pressure) to the baseline under similar conditions. The total reduction of FMEP for idle and medium load is measured to be 0.4 and 0.8 bar respectively. When the above results are applied to complete rather than single cylinder engine application, the combined fuel efficiency benefit is approximated to a fuel consumption reduction of 33 % at idle and up to 10 % for medium loads and

Dardalis, Dimitrios, Hall, Matthew, Riley, Sebastian, Basu, Amiyo, Matthews, Ron

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

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, Gitapathi, Ajinkya

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

Fully Automated Global Powertrain Optimization for Electric Truck Using Active Learning Algorithm and Backwards Simulation Approach

2025-01-8536To be published on 04/01/2025

To reduce greenhouse gas emissions, electric vehicles (EVs) are increasingly becoming a significant part of the automotive market. This trend is not limited to passenger cars, but also extending to the truck segment. Electric trucks, due to their substantial self-weight and payload, require a different approach compared to electric passenger cars. While electric passenger cars generally use only one motor or a single-speed transmission, electric trucks necessitate the use of multiple motors or multi-speed transmissions. This addresses a complex issue: how to determine the size of the motor, the number of motors, the number of gears, and the corresponding gear ratios in the drive system of an electric truck. The nonlinearity of the vehicle system further complicates this issue. To tackle this, the paper proposes the application of an active learning algorithm, namely Bayesian optimization, to determine the configuration of the motors and transmission. The goal is to provide an optimal

Chen, Bicheng, Wellmann, Christoph, Xia, Feihong, Savelsberg, Rene, Andert, Jakob, Pischinger, Stefan

Research on Multi-Objective Energy Management Strategies for Fuel Cell Commercial Vehicles

2025-01-8180To be published on 04/01/2025

Fuel cells offer several advantages, including extended range, rapid refueling, and clean and efficient, making them well-suited for long-distance transportation in commercial vehicles. A multi-objective real-time optimization energy management strategy is proposed based on the comprehensive consideration of the equivalent hydrogen consumption and energy source lifetime. Power distribution among the energy sources is achieved by minimizing the vehicle's instantaneous comprehensive operational cost. Two coefficients are employed to restrict the fuel cell's start-stop frequency and load variation range. Additionally, two control coefficients are introduced in the objective function to regulate the battery's state of charge. The analysis shows that multi-objective real-time optimization energy management strategy is 10% and 14% less economical than conventional rule-based energy management strategy in both operating conditions and 5% and 7.8% higher than dynamic programming. However, the

You, Jianhui, Gu, Zhuangzhuang, Wu, Jinglai, Zhang, Yunqing

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

Modeling and Control Strategy of Engine Cooling System for a Light Weight Commercial Vehicle

2025-01-8195To be published on 04/01/2025

The engine cooling fan, water pump and thermostat are key controllable components of the engine cooling system. In order to investigate the effects on the engine cooling system under different control strategies, a simulation model for a light weight commercial vehicle's engine cooling system is established. The simulation model takes into account the performance parameters for each component of the engine cooling system and the impact of vehicle operating conditions on the engine cooling system, with the goal of achieving the highest possible fidelity of the simulation model. The engine outlet coolant temperature and the power consumption of the engine cooling fan, water pump and thermostat are calculated at various vehicle speeds and engine loads. Comparing the simulation results with the data read from the Electric Control Unit (ECU) in the engine road tests, the simulation model’s accuracy is validated. Based on the validated model, the engine cooling system is then optimized by

Li, Bing, Li, Min, Ying, Runhai, Wang, Xinling, Duan, Yaolong, Shangguan, Wen-Bin

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

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

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)

Simulation of GHG Emissions for Production Phase of Battery Electric and Hydrogen Fuel Cell Electric HDVs under Different Electricity Grid Mixes

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 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

Bi-Level Control Co-Design for Parallel Electric-Hydraulic Hybrid Vehicles

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

This study presents a control co-design method that utilizes a bi-level optimization framework for parallel electric-hydraulic hybrid powertrains, specifically targeting heavy-duty vehicles like class 8 semi-trailer trucks. The primary objective is to minimize battery energy consumption, particularly under high torque demand at low speed, thereby extending both battery lifespan and vehicle driving range. The proposed method formulates a bi-level optimization problem to ensure global optimality in hydraulic energy storage sizing and the development of a high-level energy management strategy. Two nested loops are used: the outer loop applies a Genetic Algorithm (GA) to optimize key design parameters such as accumulator volume and pre-charged pressure, while the inner loop leverages Dynamic Programming (DP) to optimize the energy control strategy in an open-loop format without predefined structural constraints. Both loops use a single objective function, i.e. battery energy consumption

Taaghi, Amirhossein, Yoon, Yongsoon

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, Sergyjovych, Oleksandr Polianskyi, Kaidalov, Ruslan, Dubinin, Yevhen, Abramov, Dmytrii, Molodan, Andrii, Andrey, Korobko, Kholodov, Mykhailo, Omelchenko, Vasyl, Krasnokutskyi, Maksym

Development of Prediction Model for Vehicle Road Load Using Machine Learning

2025-01-8258To be published on 04/01/2025

In the modern automotive industry, improving fuel efficiency while reducing carbon emissions is a critical challenge. To address this challenge, accurately measuring a vehicle’s road load is essential. The current methodology, widely adopted by national guidelines, follows the coastdown test procedure. However, coastdown tests are highly sensitive to environmental conditions, which can lead to inconsistencies across test runs. Previous studies have mainly focused on the impact of independent variables on coastdown results, with less emphasis on a data-driven approach due to the difficulty of obtaining large volumes of test data in a short period, both in terms of time and cost. This paper presents a road load energy prediction model for vehicles using the XGBoost machine learning technique, demonstrating its ability to predict road load coefficients. The model features 27 factors, including rolling, aerodynamic, inertial resistance, and various atmospheric conditions, gathered from a

Song, Hyunseung, Lee, Dong Hyuk, Chung, Hyun

Validation of a New Road and Contact Model for Vehicle-Soft Soil Terrain Interaction through an Elaborate Modeling of the FED-Alpha Vehicle

2025-01-8800To be published on 04/01/2025

Employing multibody dynamic simulations with semi-empirical tire models is widely recognized as a cost-effective approach. A recent development introduces a novel road and tire-soil contact model that is not only swift and memory-efficient but also addresses limitations in classical semi-empirical models. This study conducts a thorough validation of the new road and contact model by creating a detailed multibody model of the four-wheeled vehicle, Fuel Efficiency Demonstrator (FED) – Alpha, integral to NATO's Next-Generation reference mobility model. The comprehensive model encompasses the chassis, suspension, tires, engine, transmission and various other components. Through simulations of various driving scenarios, accounting for complex terrain geometries, spatially varying soil properties, and multi-pass phenomena, the model's performance is evaluated. The simulation results are compared with physical measurements, providing a detailed assessment of the tire-soil model's predictive

Papapostolou, Lampros, Koutras, Evangelos, Leila, Felipe, Ribaric, Adrijan, Natsiavas, Sotirios

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

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

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

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

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

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

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, Nishida, Keiya

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

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, Thomas, Burnette, Andrew, Huang, Eddy, Alvarado, Erica, Rao, Leela

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

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