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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Neubauer, Matthias; Schildorfer, Wolfgang; Walch, Manuel; Koskinen, Sami; +1 Authors

    Autonomous vehicles will be a key ingredient of future road transport solutions. Even if significant progress has been made in technological developments and autonomous transport vehicle demonstrations, there are still challenges to be addressed before widespread adoption can occur, e.g., 24/7 availability in harsh weather conditions. Quantifying the performance of autonomous vehicles is crucial for logistics operators when deploying such solutions. This Paper presents KPIs related to autonomous road freight transport. Furthermore, the evaluation methodology of the European H2020 project AWARD related to efficiency of autonomous vehicles is presented and initial insights from the project are sketched. Presented at the 9th International Physical Internet Conference (IPIC 2023) 13-15 June 2023, Athens, Greece

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    Article . 2023
    License: CC BY
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    Conference object . 2023
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    https://doi.org/10.35090/gatec...
    Other literature type . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Danielis, R.; Giansoldati, M.; Scorrano, M.;

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Harvey, Daniel R.;

    With electric vehicles becoming increasingly prevalent in the automotive market consumers are becoming more conscientious of total driving range. In light of this trend, reliable and accurate modeling methods are necessary to aid the development of more energy efficient vehicles with greater drivable range. Many methods exist for evaluating energy consumption of current and future vehicle designs over the US certification drive cycles. This work focuses on utilizing the well-established Willans line approximation and proposes a simplified modeling method to determine electric vehicle energy consumption and powertrain efficiency. First, a backwards physics-based model is applied to determine tractive effort at the wheel to meet US certification drive cycle demand. Second, the Willans line approximation then augments the tractive effort model and parameterizes the vehicle powertrain to establish a bi-directional power flow method. This bi-directional approach separates propel and brake phases of the vehicle over the certification City and Highway drive cycles to successfully isolate the vehicle powertrain from non-intrinsic losses, such as parasitic accessory loads. The proposed method of bi-directional modeling and parameter tuning provides significant insight to the efficiency, losses, and energy consumption of a modeled electric vehicle strictly using publicly available test data. Results are presented for eight electric vehicles with production years varying from 2016 to 2021. These electric vehicles are chosen to encapsulate the electric vehicle market as performance electric vehicles to smaller commuter electric vehicles are selected. All vehicles are modeled with an accessory load constrained between 300 and 850 W and a regenerative braking ("regen") low-speed cutoff of 5 mph with six of the eight vehicles modeled with a regenerative braking fraction of 94%. The bi-directional Willans line is then tuned to reach agreement with the net EPA energy consumption test data for each vehicle with the results presented as representative of the chosen vehicle. Lastly, a transfer function relating major model inputs to the output is derived and lends considerable insight for the sensitivity of the modeling method. Sensitivity of the proposed modeling method is conducted for a 2017 BMW i3 with the model deemed reasonably resilient to changes in input parameters. The model is most sensitive to changes in powertrain marginal efficiency with a 6% decrease of marginal efficiency leading to a 0.404 kW and 0.793 kW cycle average net battery power increase for the City and Highway drive cycles respectively. Additionally, the model is also sensitive to changes in vehicle accessory load with a direct relationship between increases of vehicle accessory load to increases of cycle average net battery power for the City and Highway cycles. The sensitivity results justify the use of the proposed model as a method for evaluating vehicle energy consumption and powertrain efficiency solely using publicly available test data. Master of Science Developing robust and accurate methods for analyzing electric vehicle energy consumption and powertrain efficiency is of great interest. For the purposes of this paper, powertrain refers to a motor / inverter pair which is coupled to a simple gear reduction for torque multiplication. Many vehicles are designed with motors of varying power and torque capabilities which can present challenges when attempting to effectively compare electric vehicles from different manufacturers. The proposed modeling method presented in this work utilizes public test data to derive detailed vehicle and powertrain information. Vehicle energy consumption is also modeled and compared to net EPA test data. Eight electric vehicles are modeled with each vehicle representing a specific segment of the current electric vehicle market. A bi-directional Willans line is applied to model the propel and brake phases of each electric vehicle over the US certification drive cycles. The bi-directional approach effectively isolates the vehicle powertrain from non-intrinsic losses. From the derived powertrain parameters and modeled energy consumption, the proposed method is deemed accurate and highly useful for translating public test data to detailed vehicle information. Lastly, a sensitivity analysis is presented with the proposed method deemed reasonably resilient to changes in input parameters. The modeling method is most sensitive to changes of powertrain marginal efficiency and vehicle accessory load but constraining these inputs to reasonable ranges for electric vehicles proves sufficient.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Call Piñol, Oriol;

    Electric vehicles are becoming an increasing need since the traditional and pollutant combustion engines are about to be extinguished. The future, in the present moment, is the design of better, more efficient and less pollutant cars that allow the mobility taking into consideration the global warming. This is why IDIADA presented the Cronuz, a concept car that aims at the future being one of the most efficient aerodynamic cars ever designed. The goal of this Project is the aerodynamics study of Cronuz car developed by IDIADA. The analysis is going to be performed with GiD for pre and post processing and Kratos Multiphysics as solver and give conclusions to the work carried out

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  • Authors: Holden, Jake; Cappellucci, Jeff;

    This is the API endpoint for RouteE energy prediction, which can be used to get both single vehicle link or route energy estimates and transportation network-wide energy consumption estimates for a variety of vehicles. This enables external researchers and transportation engineers to access and utilize NREL's growing library of pre-trained vehicle models for prediction of transportation energy consumption. This API provides three endpoints: ��� /route: Energy estimation of a vehicle over a planning link or sequence of links (route). ��� /network: Network-wide estimation of energy consumption for all vehicle traffic in the desired area. ��� /compass: Energy-optimal ���eco-routing��� between input origin and destination coordinates (Currently in beta for Denver metro area only).

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  • For multiple studies of vehicle demand, the parameters reported in the studies were used to calculate willingness to pay for a range of vehicle attributes, including performance and fuel economy.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Radosavljević Dušan M.; Manojlović Aleksandar V.; Medar Olivera M.; Bojović Nebojša J.;

    This paper presents the research on vehicle fleet energy efficiency impact upon overall vehicle effectiveness. Transport companies and companies with own vehicle fleets tend to enhance their resource effectiveness, and to increase their transport service quality with the objective of attaining a competitive position on the market. Since energy consumed for transport operations is an important transport process resource, a method for assessing transport process effectiveness has been developed with the objective of increasing vehicle fleet effectiveness and its energy efficiency, and the overall vehicle effectiveness human indicator has been defined accordingly. The developed method was then implemented in an actual vehicle fleet and variations of the overall vehicle effectiveness human indicator were researched, as well as specific energy consumptions for respective net transport volumes depending on the following indicators: vehicle payload capacity utilization rate and mileage utilization rate. It is shown that specific energy consumption influences overall vehicle effectiveness depending on both the payload capacity utilization rate and mileage utilization rate. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 36010: Development of the Model for Managing the Vehicle Technical Condition in Order to Increase its Energy Efficiency and Reduce Exhaust Emissions]

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    Authors: Sun, Peikun; Stensson Trigell, Annika; Drugge, Lars; Jerrelind, Jenny;

    An active energy-efficient direct yaw moment control (DYC) for in-wheel motor electricvehicles taking motor efficiency maps into consideration is proposed in this paper. The potentialcontribution of DYC to energy saving during quasi-steady-state cornering is analysed. The study inthis paper has produced promising results which show that DYC can be used to reduce the powerconsumption while satisfying the same cornering demand. A controller structure that includes adriver model and an offline torque distribution law during continuous driving and cornering isdeveloped. For comparison, the power consumption of stability DYC is also analysed. Simulations fordouble lane change manoeuvres are performed and driving conditions either with a constant velocityor with longitudinal acceleration are designed to verify the effectiveness of the proposed controller indifferent driving situations. Under constant velocity cornering, since the total torque demand is nothigh, two rear wheels are engaged and during cornering it is beneficial to distribute more torque toone wheel to improve energy efficiency. In the simulated driving manoeuvres, up to 10% energy canbe saved compared to other control methods. During acceleration in cornering, since the total torquedemand is high, it is energy-efficient to use all the four in-wheel motors during cornering. QC 20200224

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    Energies
    Article . 2020
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      Article . 2020
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    Authors: de Carvalho Pinheiro, H.; Galanzino, E.; Messana, A.; Sisca, L.; +3 Authors
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    https://doi.org/10.4271/2019-3...
    Conference object . 2020 . Peer-reviewed
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      https://doi.org/10.4271/2019-3...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ferraris, A.; de Carvalho Pinheiro, H.; Galanzino, E.; Airale, A. G.; +1 Authors

    Powertrain electrification is undoubtedly recognized as a major trend in the automotive industry. The elimination of the internal combustion engine opens to different vehicles architecture designs, to improve habitability and reduce cost. The paper focus on an All-Wheel-Drive Full Electric high-performance vehicle equipped with wheel-hub motors, a layout that offers a significant potential in controlling each wheel individually. The objective is to develop a control algorithm capable of handling wheels torques independently to enhance vehicle's dynamic, keeping into consideration the model's energy performance. The control algorithm is entirely developed in Matlab-Simulink and implemented in the vehicle dynamic model, in a co-simulation environment with VI-CarRealTime software. Offline simulations are performed to tune the controllers and evaluate their impact on vehicle dynamics and energy efficiency. Finally, the model is tested in a real static simulator to be validated and to have a subjective interpretation of the dynamic behavior of the vehicle. Handling improvements are evaluated through a racetrack lap time performed by the VI-Grade virtual driver. Energy efficiency protocols instead will be assessed by monitoring the battery State of Charge variation and their impact on vehicle's behavior will be analyzed on the static simulator. The results point out to an improvement in the lap time thanks to the more agile and less understeering vehicle. Energy optimization algorithms and regenerative braking displays a promising energy reduction without compromising vehicle dynamics. The same racetrack from the offline simulations is used to test the model on the static simulator. Torque vectoring impact on driver's feeling is found to be noticeable and helpful in improving vehicle's response during cornering while energy optimization protocols are not affecting the dynamic performance.

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    https://doi.org/10.1109/ev.201...
    Conference object . 2019 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Neubauer, Matthias; Schildorfer, Wolfgang; Walch, Manuel; Koskinen, Sami; +1 Authors

    Autonomous vehicles will be a key ingredient of future road transport solutions. Even if significant progress has been made in technological developments and autonomous transport vehicle demonstrations, there are still challenges to be addressed before widespread adoption can occur, e.g., 24/7 availability in harsh weather conditions. Quantifying the performance of autonomous vehicles is crucial for logistics operators when deploying such solutions. This Paper presents KPIs related to autonomous road freight transport. Furthermore, the evaluation methodology of the European H2020 project AWARD related to efficiency of autonomous vehicles is presented and initial insights from the project are sketched. Presented at the 9th International Physical Internet Conference (IPIC 2023) 13-15 June 2023, Athens, Greece

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    https://doi.org/10.35090/gatec...
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      https://doi.org/10.35090/gatec...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Danielis, R.; Giansoldati, M.; Scorrano, M.;

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Harvey, Daniel R.;

    With electric vehicles becoming increasingly prevalent in the automotive market consumers are becoming more conscientious of total driving range. In light of this trend, reliable and accurate modeling methods are necessary to aid the development of more energy efficient vehicles with greater drivable range. Many methods exist for evaluating energy consumption of current and future vehicle designs over the US certification drive cycles. This work focuses on utilizing the well-established Willans line approximation and proposes a simplified modeling method to determine electric vehicle energy consumption and powertrain efficiency. First, a backwards physics-based model is applied to determine tractive effort at the wheel to meet US certification drive cycle demand. Second, the Willans line approximation then augments the tractive effort model and parameterizes the vehicle powertrain to establish a bi-directional power flow method. This bi-directional approach separates propel and brake phases of the vehicle over the certification City and Highway drive cycles to successfully isolate the vehicle powertrain from non-intrinsic losses, such as parasitic accessory loads. The proposed method of bi-directional modeling and parameter tuning provides significant insight to the efficiency, losses, and energy consumption of a modeled electric vehicle strictly using publicly available test data. Results are presented for eight electric vehicles with production years varying from 2016 to 2021. These electric vehicles are chosen to encapsulate the electric vehicle market as performance electric vehicles to smaller commuter electric vehicles are selected. All vehicles are modeled with an accessory load constrained between 300 and 850 W and a regenerative braking ("regen") low-speed cutoff of 5 mph with six of the eight vehicles modeled with a regenerative braking fraction of 94%. The bi-directional Willans line is then tuned to reach agreement with the net EPA energy consumption test data for each vehicle with the results presented as representative of the chosen vehicle. Lastly, a transfer function relating major model inputs to the output is derived and lends considerable insight for the sensitivity of the modeling method. Sensitivity of the proposed modeling method is conducted for a 2017 BMW i3 with the model deemed reasonably resilient to changes in input parameters. The model is most sensitive to changes in powertrain marginal efficiency with a 6% decrease of marginal efficiency leading to a 0.404 kW and 0.793 kW cycle average net battery power increase for the City and Highway drive cycles respectively. Additionally, the model is also sensitive to changes in vehicle accessory load with a direct relationship between increases of vehicle accessory load to increases of cycle average net battery power for the City and Highway cycles. The sensitivity results justify the use of the proposed model as a method for evaluating vehicle energy consumption and powertrain efficiency solely using publicly available test data. Master of Science Developing robust and accurate methods for analyzing electric vehicle energy consumption and powertrain efficiency is of great interest. For the purposes of this paper, powertrain refers to a motor / inverter pair which is coupled to a simple gear reduction for torque multiplication. Many vehicles are designed with motors of varying power and torque capabilities which can present challenges when attempting to effectively compare electric vehicles from different manufacturers. The proposed modeling method presented in this work utilizes public test data to derive detailed vehicle and powertrain information. Vehicle energy consumption is also modeled and compared to net EPA test data. Eight electric vehicles are modeled with each vehicle representing a specific segment of the current electric vehicle market. A bi-directional Willans line is applied to model the propel and brake phases of each electric vehicle over the US certification drive cycles. The bi-directional approach effectively isolates the vehicle powertrain from non-intrinsic losses. From the derived powertrain parameters and modeled energy consumption, the proposed method is deemed accurate and highly useful for translating public test data to detailed vehicle information. Lastly, a sensitivity analysis is presented with the proposed method deemed reasonably resilient to changes in input parameters. The modeling method is most sensitive to changes of powertrain marginal efficiency and vehicle accessory load but constraining these inputs to reasonable ranges for electric vehicles proves sufficient.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Call Piñol, Oriol;

    Electric vehicles are becoming an increasing need since the traditional and pollutant combustion engines are about to be extinguished. The future, in the present moment, is the design of better, more efficient and less pollutant cars that allow the mobility taking into consideration the global warming. This is why IDIADA presented the Cronuz, a concept car that aims at the future being one of the most efficient aerodynamic cars ever designed. The goal of this Project is the aerodynamics study of Cronuz car developed by IDIADA. The analysis is going to be performed with GiD for pre and post processing and Kratos Multiphysics as solver and give conclusions to the work carried out

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  • Authors: Holden, Jake; Cappellucci, Jeff;

    This is the API endpoint for RouteE energy prediction, which can be used to get both single vehicle link or route energy estimates and transportation network-wide energy consumption estimates for a variety of vehicles. This enables external researchers and transportation engineers to access and utilize NREL's growing library of pre-trained vehicle models for prediction of transportation energy consumption. This API provides three endpoints: ��� /route: Energy estimation of a vehicle over a planning link or sequence of links (route). ��� /network: Network-wide estimation of energy consumption for all vehicle traffic in the desired area. ��� /compass: Energy-optimal ���eco-routing��� between input origin and destination coordinates (Currently in beta for Denver metro area only).

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