• August 2019
    Our new paper "Effects of ambient temperature on the route planning of electric freight vehicles" (with Sina Rastani and Bülent Çatay) is now available on Transportation Research Part D.
  • 2019
    Looking for highly motivated undergraduate and graduate students to work in projects related with vehicle electrification, battery system design, and battery systems modeling. If you are interested, please contact me via e-mail. You can find the necessary information about graduate applications here.
  • March 2019
    Future Seminar Series
    I gave a seminer titled "Electric Mobility: Shaping the Sustainable Future" in Future Seminar Series organized by ADP Team at Sabanci University. You can watch it here.
  • Feb. 2019
    IAEC '19
    I joined the organizing committee for IAEC '19. Stay tuned for the program.


  • 2015 2010

    Ph.D. in Mechanical Engineering

    Carnegie Mellon University

    Thesis title: Quantification of Temperature Implications and Investigation of Battery Design Options for Electrified Vehicles

  • 2010 2007

    M.Sc. in Mechanical Engineering

    Middle East Technical University

    Thesis title: Modeling and Simulation of High-Speed Railway Dynamics

  • 2007 2003

    B.S. in Mechanical Engineering

    Middle East Technical University

Honors, Awards and Grants

  • 2017-2018
    Sabanci University Internal Research Grant
    Cost and Benefits of Vehicle Electrification in Turkey
  • 2016-2018
    Tubitak 2232 - Returning Scientist Program
    Comparison of Battery Thermal Management Techniques In Terms of Their Effects on Battery Life in Electrified Vehicles, and Investigating the Role of Operating Conditions on this Comparison
  • 2010-2012
    Fulbright Scholarship
    Support for Ph.D. study in United States for two academic years
  • 2007-2010
    Graduate Fellowship of Scientific and Technical Research Council of Turkey
    Partial support for M.Sc. study in Turkey for three academic years

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Effects of ambient temperature on the route planning of electric freight vehicles

S.Rastani, T. Yuksel, B.Catay
Journal Paper Transportation Research Part D: Transport and Environment, 2019, Volume 74, Pages 124-141


Electric freight vehicles have strong potential to reduce emissions stemming from logistics operations; however, their limited range still causes critical limitations. Range anxiety is directly related to the total amount of energy consumed during trips. There are several operational factors that affect the energy consumption of electric vehicles and should be considered for accurate route planning. Among them, ambient temperature arises as a key factor because cabin heating or cooling may significantly increase the energy discharged from the battery during the trip and reduce the driving range. Additionally, cold temperatures decrease the battery efficiency and cause performance losses. In this study, we investigate the effect of ambient temperature on the fleet composition, energy consumption, and routing decisions in last-mile delivery operations. First, we present the mathematical programming formulation of the problem. Next, we perform an extensive computational study based on benchmark data from the literature. For solving the small-size instances we use a commercial solver. For solving the large-size instances we employ an adaptive large neighborhood search algorithm. Our results show that the route plans made without considering the ambient temperature effect may lead to inefficient operations and disruptions. Specifically, the fleet size and energy consumption can increase by 46% and 81%, respectively, in small-size problems on average due to ambient temperature whereas the average increase can reach 15% and 68%, respectively, in large-size problems. Finally, we present a case study from a logistics company operating in Southern Turkey to provide managerial insights to both researchers and practitioners.

Plug-in Hybrid Electric Vehicle LiFePO4 Battery Life Implications of Thermal Management, Vehicle Design, Driving Conditions, and Regional Climate

T. Yuksel, V. Viswanathan, S. Litster, J.J. Michalek
Journal Paper Journal of Power Sources, 2017, Volume 338, Pages 49-64


Battery degradation strongly depends on temperature, and many plug-in electric vehicle applications employ thermal management strategies to extend battery life. The effectiveness of thermal management depends on the design of the thermal management system as well as the battery chemistry, cell and pack design, vehicle system characteristics, and operating conditions. We model a plug-in hybrid electric vehicle with an air-cooled battery pack composed of cylindrical LiFePO4/graphite cells and simulate the effect of thermal management, driving conditions, regional climate, and vehicle system design on battery life. We estimate that in the absence of thermal management, aggressive driving can cut battery life by two thirds; a blended gas/electric-operation control strategy can quadruple battery life relative to an all-electric control strategy; larger battery packs can extend life by an order of magnitude relative to small packs used for all-electric operation; and batteries last 73–94% longer in mild-weather San Francisco than in hot Phoenix. Air cooling can increase battery life by a factor of 1.5–6, depending on regional climate and driving patterns. End of life criteria has a substantial effect on battery life estimates.

Effect of regional grid mix, driving patterns and climate on the comparative carbon footprint of gasoline and plug-in electric vehicles in the United States

T. Yuksel, M.M. Tamayao, C. Hendrickson, I. Azevedo, J.J. Michalek
Journal Paper Environmental Research Letters, 2016, Volume 11, Issue 4, Pages 044007


We compare life cycle greenhouse gas (GHG) emissions from several light-duty passenger gasoline and plug-in electric vehicles (PEVs) across US counties by accounting for regional differences due to marginal grid mix, ambient temperature, patterns of vehicle miles traveled (VMT), and driving conditions (city versus highway). We find that PEVs can have larger or smaller carbon footprints than gasoline vehicles, depending on these regional factors and the specific vehicle models being compared. The Nissan Leaf battery electric vehicle has a smaller carbon footprint than the most efficient gasoline vehicle (the Toyota Prius) in the urban counties of California, Texas and Florida, whereas the Prius has a smaller carbon footprint in the Midwest and the South. The Leaf is lower emitting than the Mazda 3 conventional gasoline vehicle in most urban counties, but the Mazda 3 is lower emitting in rural Midwest counties. The Chevrolet Volt plug-in hybrid electric vehicle has a larger carbon footprint than the Prius throughout the continental US, though the Volt has a smaller carbon footprint than the Mazda 3 in many urban counties. Regional grid mix, temperature, driving conditions, and vehicle model all have substantial implications for identifying which technology has the lowest carbon footprint, whereas regional patterns of VMT have a much smaller effect. Given the variation in relative GHG implications, it is unlikely that blunt policy instruments that favor specific technology categories can ensure emission reductions universally.

Effects of regional temperature on electric vehicle efficiency, range, and emissions in the United States

T. Yuksel, J.J. Michalek
Journal Paper Environmental Science and Technology, 2015, Volume 49, Issue 6, Pages 3974-3980


We characterize the effect of regional temperature differences on battery electric vehicle (BEV) efficiency, range, and use-phase power plant CO2 emissions in the U.S. The efficiency of a BEV varies with ambient temperature due to battery efficiency and cabin climate control. We find that annual energy consumption of BEVs can increase by an average of 15% in the Upper Midwest or in the Southwest compared to the Pacific Coast due to temperature differences. Greenhouse gas (GHG) emissions from BEVs vary primarily with marginal regional grid mix, which has three times the GHG intensity in the Upper Midwest as on the Pacific Coast. However, even within a grid region, BEV emissions vary by up to 22% due to spatial and temporal ambient temperature variation and its implications for vehicle efficiency and charging duration and timing. Cold climate regions also encounter days with substantial reduction in EV range: the average range of a Nissan Leaf on the coldest day of the year drops from 70 miles on the Pacific Coast to less than 45 miles in the Upper Midwest. These regional differences are large enough to affect adoption patterns and energy and environmental implications of BEVs relative to alternatives.

Modeling and Simulation of High Speed Railway Vehicle Dynamics

T. Yuksel, Y.S. Unlusoy
Conference Paper Proceedings of International Congress on Advanced Railway Engineering, Istanbul, TURKEY, 2015, March 02-04.


This study aims to provide mathematical model(s) for the simulation of high speed railway vehicles. The dynamic behavior of a high speed train is divided into three uncoupled motions: vertical, lateral, and longitudinal. Two models with different complexities are used to simulate vertical plane response of the vehicle to track vertical irregularities. Different wheel-rail contact formulations are utilized to simulate the lateral plane motion of the vehicle on tangent and curved tracks. For both vertical and lateral dynamics modeling, a single wagon is assumed to simulate the whole vehicle. Finally, wagon interactions are taken into account and the response of a full train to different traction/braking inputs are analyzed. The models are parametric and they are used to develop computer programs to simulate train motion. Using a set of parameters obtained from literature, different case studies were performed to test model functionality. It was observed that 10 degree of freedom model can predict the vertical behavior quite well. In wheel-rail contact modeling, the nonlinearities should be included in the system and the wheel profile with its tread and flange sections should be introduced to obtain accurate results. Finally, in longitudinal dynamics modeling, the stopping time and distance between wagons with respect to braking delay and wagon to wagon connection are examined.

A moving horizon state estimator in the control of thermostatically controlled loads for demand response

E.C. Kara, Z. Kolter, M. Berges, B. Krogh, G. Hug, T. Yuksel
Conference Paper Smart Grid Communications (SmartGridComm), 2013 IEEE International Conference.


The quality and effectiveness of the load following services provided by centralized control of thermostatically controlled loads depend highly on the communication requirements and the underlying cyberinfrastructure characteristics. Specifically, ensuring end-user comfort while providing real-time demand response services depends on the availability of the information provided from the thermostatically controlled loads to the main controller regarding their operating statuses and internal temperatures. State estimation techniques can be used to infer the necessary information from the aggregate power consumption of these loads, replacing the need for an upstream communication platform carrying information from appliances to the main controller in real-time. In this paper, we introduce a moving horizon mean squared error state estimator with constraints as an alternative to a Kalman filter approach, which assumes a linear model without constraints. The results show that some improvement is possible for scenarios when loads are expected to be toggled frequently.

Development of a simulation model to analyze the effect of thermal management on battery life

T. Yuksel, J. J. Michalek
Conference Paper SAE Technical Paper 2012-01-0671.


Battery life and performance depend strongly on temperature; thus there exists a need for thermal conditioning in plug-in vehicle applications. The effectiveness of thermal management in extending battery life depends on the design of thermal management used as well as the specific battery chemistry, cell and pack design, vehicle system characteristics, and operating conditions. We examine the case of an air cooled plug-in hybrid electric vehicle battery pack with cylindrical LiFePO4/graphite cell design and address the question: How much improvement in battery life can be obtained with passive air cooling? To answer this question, a model is constructed consisting of a thermal model that calculates temperature change in the battery and a degradation model that estimates capacity loss. A driving and storage profile is constructed and simulated in two cities - Miami and Phoenix - which have different seasonal temperatures. The results suggest that air cooling may extend battery life by 5% in Miami, characterized by higher average temperatures, and by 23% in Phoenix, characterized by higher peak temperatures. Thus, thermal management appears to have the greatest effect in regions with high peak temperatures, even if the region has lower average temperatures.

Evaluation of the Effects of Thermal Management on Battery Life in Plug-in Hybrid Electric Vehicles

T. Yuksel, J. J. Michalek
Conference Paper Proceedings of Battery Congress 2012, Ann Arbor, Michigan, USA, April 23-24.


We develop a simulation model that aims to evaluate the effect of thermal management on battery life. The model consists of two sub- models: a thermal model and a battery degradation model. The temperature rise in the battery is calculated using the thermal model, and a temperature profile is obtained under pre-defined driving, charging and stand-by scenarios. The temperature profile and the energy requirement required to achieve a driving profile act as inputs to the degradation sub-model, which is used to predict the battery life. The degradation model is derived from models and test data available in literature, and the model is constructed for air- cooled cylindrical LiFePO4 cells based on the Hymotion Prius-conversion configuration. Preliminary results suggest that peak temperatures have the greatest impact on degradation: Thermal management increases life substantially in climates with high peak temperatures (Pheonix) and for more aggressive driving cycles (US06), while thermal management has less influence in climates with lower peak temperatures (Miami) and with gentle driving cycles (UDDS). Use of cabin air vs. outside air for thermal management has minor impact on battery life for the control strategy used, but thermostat control settings are important for lowering peak temperatures and extending battery life.

Polymorphic robotic system controlled by an observing camera

B. Kocer, T. Yuksel, M.E. Yumer, C.A. Ozen, U. Yaman
Conference Paper The 2nd International Conference on Digital Image Processing (ICDIP), Singapore, 2010, February 26-28.


Polymorphic robotic systems, which are composed of many modular robots that act in coordination to achieve a goal defined on the system level, have been drawing attention of industrial and research communities since they bring additional flexibility in many applications. This paper introduces a new polymorphic robotic system, in which the detection and control of the modules are attained by a stationary observing camera. The modules do not have any sensory equipment for positioning or detecting each other. They are self-powered, geared with means of wireless communication and locking mechanisms, and are marked to enable the image processing algorithm detect the position and orientation of each of them in a two dimensional space. Since the system does not depend on the modules for positioning and commanding others, in a circumstance where one or more of the modules malfunction, the system will be able to continue operating with the rest of the modules. Moreover, to enhance the compatibility and robustness of the system under different illumination conditions, stationary reference markers are employed together with global positioning markers, and an adaptive filtering parameter decision methodology is enclosed. To the best of authors' knowledge, this is the first study to introduce a remote camera observer to control modules of a polymorphic robotic system.

Current Teaching

  • Fall 2018

    ENS 207 - Introduction to Energy Systems

    This course is concerned with the generation of power and utilization of energy for the benefits of the society in industry, transportation and domestic use. The scope of this course includes fundamental principles and analysis of energy systems. Students will learn to use the fundamental principles that are used in the analysis of energy systems. Specifically selected topics from thermodynamics, fluid mechanics and heat transfer will be subjects of this course. Particular topics include but not limited or exclusive to: conservation of mass and energy, control volumes and control surfaces, the second law of thermodynamics, entropy, and efficiency analysis of heat engines.

  • Spring 2019

    ME 441/541 - Advanced Vehicle Systems

    This course aims to provide basic concepts towards understanding electri ed vehicles. It aims to provide the students the technical fundamentals to build models and perform simplified dynamics and control analyses.

  • Spring 2019

    ENS 315 - Energy

    This course aims to provide basic concepts towards understanding the world energy problems, renewable and non-renewable energy sources, their advantages, shortcomings and impacts to the environment.

  • Spring 2019

    ETM 518: Energy and Mobility

    Basics of the transportation technology. Energy and environmental effects of transportation. Low carbon fuels and vehicle technologies with reduced climate impact, and their interaction with energy sources. Smart and integrated mobility solutions and their prospective effects in energy use and security. Current and future transportation policies, their economic, societal and environmental interactions.

Teaching History

  • ENS 207 - Introduction to Energy Systems (Fall 2017)

    ENS 315 - Energy (Spring 2017/2018)