• Lea Pavelko , 2021-, Supervisor: Joško Deur, Ph. D. Thesis connected with project Safe Speed Anticipating for Encountering Pedestrian Crossing.
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• Jure Soldo, 2020-2023, Supervisor: Joško Deur, Ph. D. Thesis connected with project Adaptive and Predictive Control of Plug-in Hybrid Electric Vehicles (ACHIEVE).

Ivan Cvok, 2018-2022, Supervisor: Joško Deur, Ph. D. Thesis connected with project Qualifying and Implementing a User-centric Designed and Efficient Electric Vehicle (QUIET).

Vanja Ranogajec, 2015-2019, Supervisor: Joško Deur, Ph. D. Thesis connected with project Optimization of Automatic Transmission Shift Control.

Synthesis of safety mechanism for model predictive control of autonomous vehicle approaching unsignalized crosswalk with pedestrians, B. Škugor, 2023.

Application of machine learning to predict state variables related to driving autonomous vehicles, J. Deur, 2022.

Lithium-ion Battery Aging Characterization in a Realistic Simulation Environment, J. Deur, 2021.

• Application of optimization methods in the design of mechanisms including experimental verification, M. Hoić, 2021.

Data-Driven Modeling of Electric Vehicle Lithium-Ion Battery Aging, J. Deur, 2020.  

• Experimental verification of strength and rigidity of organically formed structures, M. Hoić, 2020.
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• Experimental Characterization of Electric Scooter Li-Ion Battery Pack Aging,  J. Deur, 2019.
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• Development of a mathematical model for the optimal design of the portal crane, M. Hoić, 2019.

Parameter Estimation of an Electric Scooter Li-Ion Battery Pack Model, J. Deur, 2018.

Modeling of Synchronizer Dynamics for Dual Clutch Automatic Transmission, M. Hoić, 2018.

Experimental Characterization and Modelling of an Electric Scooter Li-Ion Battery Pack, J. Deur, 2017.

Optimal Control of Dual Clutch Hybrid Transmissions, J. Deur, 2016.

Optimal Control of Hybrid Electric Vehicles under Conditions of Emphasized Road Gradients, J. Deur, 2015.

Energy Efficient Hydraulics: Principles, Measurements and Cost-effectiveness, J. Petrić, 2014.

Energy Flow Control of Electric Microgrid for Oil Drilling Rig, D. Pavković, 2013

Research project supported through University Research Program (URP) of Ford Motor Company

Period: 2022-2023

Project team: Automotive Control Group of The University of Zagreb-FMENA

Project leader: Prof. Joško Deur, Ph.D.

Project scope:

• Developing a vehicle model that incorporates clutch synchronization loss for straight-line driving analysis.
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• Conducting optimization of motor torque and clutch states to balance energy savings with component durability.
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• Developing and evaluating rule-based and model predictive control strategies against dynamic programming-optimized benchmarks for energy efficiency.
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Research project supported through T-HT Comapny - Zagreb, Croatia

Period: 2021-2022

Project team: Automotive Control Group of The University of Zagreb-FMENA

Project leader: Prof. Joško Deur, Ph.D.

Project scope:

• Analysis for bus electrification in Rijeka

Integration with SmartCity.SURINMO for advanced transport systems

Optimal configuration of electrified transport

Technical-economic analysis of fleet ownership costs

Research project supported through University Research Program (URP) of Ford Motor Company

Period: 2020-2023

Project team: Automotive Control Group of The University of Zagreb-FMENA

Project leader: Prof. Joško Deur, Ph.D.

Project scope:

• Agent-based modelling of multi-vehicle and multi-pedestrian interactions at crosswalks
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• Developing machine learning model for predicting multi-agent behaviour at crosswalks 
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• Design of control system aimed to provide vehicle safe speed while approaching crosswalk
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• Adaptation of control system to reflect varying behaviour of pedestrians

Research project supported through University Research Program (URP) of Ford Motor Company

Period: 2014-2016

Project team: Automotive Control Group of The University of Zagreb-FMENA

Project leader: prof. dr. sc. Joško Deur

Project scope:

Numerical optimization of shift control variables

Design of optimal feedforward and feedback shift-control laws and verification against optimization benchmark

Optimization of control law parameters for robust behavior

Numerical optimization of shift scheduling

Project Acronym: i-RESEV

Project Website: hrzz.hr/default.aspx?id=2344

Period: 2012 -

Summary: Due to the intermittent nature of renewable energy sources (RES), the related energy systems need to include significant backup in terms of traditional energy sources or a significant electric storage capacity. This increases the cost of electrical energy and the overall energy system and hinders the RES proliferation. The growing presence of electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) brings a substantial amount of distributed battery storage capacity that is connected to the grid (vehicle-to-grid concept, V2G), thereby opening new opportunities for the RES integration. However, the overall transport and energy system (TES) becomes more complex and it can be optimally managed only by way of a widespread involvement of information and communication technologies (ICT).

The main objective of the proposed project is to provide a basis for full integration of EVs into the RES-based energy systems, through extensive use of ICTs in: (i) modelling, simulation, and optimisation processes; (ii) on-line optimal control, estimation, and prediction; (iii) strategic planning; and (iv) supporting services.

There are two distinctive research and development (R&D) paths towards realising the goal of predeployment and wider uptake of smart connected electromobility, which will propel future transport and energy systems towards sustainability. The first path is focused on solving the problem on the energy system level (top-down approach) in terms of optimising the use of RES, having in mind benefits and requirements of electrified transport. The second (bottom-up) approach is aimed at optimising the EV energy management control (EMC) system, with the goal to minimise the fuel and electricity consumption for given grid parameters and a-priori

Clearly, as these basic individual efforts evolve and the ICTs become more sophisticated, there is a need for a comprehensive approach to planning, design and control of the overall TES, in order to approach the optimal behaviour for given operating parameters. To achieve this goal, the proposed project assembles a multidisciplinary team of automotive control and energy system planning researchers with a significant international experience.

The proposed research approach starts with optimal design of EV control strategy. The optimised EV system is simulated for a variety of realistic 24-hour driving cycles. The obtained data are used to develop a probabilistic model of the electric transport system, which is linked to energy system planning models to optimise energy system components and V2G operation. Finally, the overall TES model is used for assessment of various RES-grid-EV configurations.

Project Newsletters:

1st Newsletter - September 2012

2nd Newsletter - August 2013

3rd Newsletter - December 2013

4th Newsletter - September 2014

5th Newsletter - December 2014

Project number: 120-1201773-1771

Period: January 2007 - 2012

Summary: Introduction of vehicle dynamics control systems (ABS, TCS, ESP, ARC, CDC. etc.) leads to substantial improvements in vehicle safety for critical manoeuvres, ride comfort, and handling performance. Commercial solutions of these systems are based on traditional ABS hydraulic-brake actuators. Development and application of new actuators, such as active steering, active differential, and active suspension have led to intensifying the research activities with the aim of further improvements of vehicle dynamics control performance. Control system requires knowledge of various vehicle dynamics quantities, whose measurements are often difficult or expensive. It is, therefore, necessary to develop precise vehicle dynamics estimators. The development of the controllers and estimators relies on mathematical models of vehicle dynamics. These models need to have simple structure which faithfully describes basic vehicle dynamics modes.

The aims of the proposed research are: (a) development of precise control-oriented vehicle dynamics models with emphasis on tyre models; (b) development of vehicle dynamics estimators based on the so-called sensor fusion concept (fusion of ABS sensors, accelerometers, gyroscopes, and GPS); (c) design and comparative analysis of vehicle dynamics control systems for various configurations of actuators and sensors. The project should, thus, give clear answers about the level of driving safety, comfort and performance improvements based on the application of advanced actuators and sensors, as well as about optimal structures of estimators and controllers needed to achieve this goal. The final research results would be faithful nonlinear and linearised models of tyre and vehicle dynamics, and optimal systems of vehicle dynamics estimation and control for various control tasks.

The proposed models, estimators and controllers are planned to be verified by computer simulation and experiment. The experimental verifications will be carried out by using the present Faculty's test vehicle with an in-wheel electrical servo-motor. Depending on available financial resources, the vehicle would be extended with a direct drive for steering, as well as with many advanced tyre and vehicle dynamics sensors.

The research results can found direct applications in automotive industry, and also in railway-vehicle and overall transportation industries. The research should give a contribution to global efforts for increasing the transportation safety.

Project number: 120-0361621-1896

Period: January 2007 - 2012

Summary: Hybrid vehicle drive has generally been accepted as an effective solution for the improvement of both vehicle power management, and the requirement on the reduction of emission gasses. These represent two most important issues in modern vehicles. It is also important to satisfy the opposing expectations of the driver with respect to good vehicle driving performance, comfort, safety, and vehicle fuel autonomy.

Hybrid vehicles usually utilize several different power sources. Typically, an internal combustion engine is combined with an electrical motor (with possible additional generator unit), and appropriate devices for energy storage such as chemical batteries and/or ultracapacitors. Thus, they are capable of facilitating considerable reduction in power consumption and lower emissions by means of high efficiency of ICE operation, vehicle kinetic energy storage during braking, and utilization of relatively small.

The principal problem of hybrid vehicle design is the optimal combination of hybrid drive elements, and the development of the power management strategy for several different power sources. Vehicle power management and control is rather complex and it equally depends on the vehicle itself, the driver, and the driving conditions.

An alternative to hybrid electric vehicle is a hybrid hydraulic vehicle. A hydraulic unit (motor/pump) is utilized with the so-called hydropneumatic accumulator unit for energy storage during vehicle braking. The implementation of hybrid hydraulic drives may be potentially valuable for a medium/large-scale vehicles which usually operate in stop-and-go regime (urban delivery vehicles, waste disposal vehicles, small trucks and vans, small busses and similar).

As the individual vehicle subsystems become increasingly integrated, their effect on the overall vehicle drive becomes more and more emphasized. For instance, the implementation of antilock braking system, traction control, or dynamic stability control system can be quite different in hybrid vehicles compared to standard vehicles. Furthermore, there is also a wide range of additional mechatronic systems in vehicles, such as active differentials, assisted launch systems, active suspension systems and other systems that may affect the overall vehicle performance. It is anticipated that these mechatronic systems may have significant influence on hybrid vehicle drive, so a whole new range of vehicle control system applications can be expected.

Based on the above elaboration, the major tasks of this project will be the estimation and control of hybrid electrical vehicles, the analysis of feasible hybrid vehicle performance, and the research of hybrid hydraulic vehicle control. In addition, a significant portion of this project will also be dedicated to analysis, modeling and control of vehicle mechatronic subsystems.

Project number:

Period: 2007 - 2011

Summary: Friction represents motion resistance of two surfaces in the contact, and it determines significantly the characteristics of many technical systems and elements. There are numerous examples, with useful and harmful effects.

The coefficients or forces determine the friction, and with their thorough knowledge the systems or products affected by the friction can be considerably improved. That can be achieved by better construction and materials, or even with better control methods, which is particularly emphasized currently.

The experimental analysis is the only way to have reliable information about the friction coefficients and forces. Special machines - tribometers have been applied for that purpose. In most cases tribometers are oriented for statically friction analysis, i.e. when the general conditions of friction have not been changing during the test procedure. Sometimes dynamical, variable conditions can be of particular interest. For example normal force, relative velocity, or dwell time can be variable, and nonlinear effects like Stribeck can be interesting, too.

For such experiments and test procedures, this project proposes the numerically controlled machine for friction analysis, which is characterized by very fast dynamics, high accuracy, versatility and automation of measuring procedures. That is owing to fast servo-drives, precise measuring equipment, variability of sliding surfaces and specifically developed control algorithms and measuring procedure.

Project number: 0120-053

Period: June 2002 - Summary:

The application of various control systems of ground vehicles results in significant improvement of drivability, safety, comfort, fuel economy, and emissions. The development of automotive control systems is based on the knowledge of mathematical models of automotive elements and systems. Since a control system often requires knowledge of power train quantities which cannot be measured conveniently, it is necessary to develop on-line estimators of these quantities.

In the known models of automotive elements and systems, some important dynamics effects are often neglected (e.g. dynamics of friction in clutches, servo-system gears, and tires), or the models are too complex from the standpoint of control system development (e.g. finite-element-based models). Development of simple, physical, control-oriented, and experimentally validated dynamic models of automotive power trains is proposed in this project. Alternatively, the application of black-box models based on the neural nets is to be considered. The emphasis is given on modeling of engine, electronic throttle body, wet clutch of an automatic transmission, and tire. A detailed analysis of the dynamic behavior of these elements and the overall power train with automatic transmission is carried out, in order to facilitate model parameterization and control system design.

Estimation of engine torque, vehicle traction force, and other quantities of an automotive power train is usually conducted in the open loop. Design and experimental examination of closed-loop nonlinear estimators are proposed in this project, in order to increase static and dynamic accuracy of estimation in the presence of emphasized process parameters variations. A special attention is given to the choice of estimator structure which would provide estimator robustness 

Based on the developed models and estimators, various high-performance automotive control systems are designed and experimentally verified. An emphasis is on idle speed control, active compensation of combustion pulses in hybrid vehicles, servo-control of electronic throttle, and vehicle dynamics control systems including ABS and traction control.

Project number: TP-106/2001

Period: 2002-2003

Summary: Faithful mathematical models of automotive power trains are necessary for development of different automotive control systems. The project includes improvements and extensions of dynamic models of basic elements of power trains with automatic transmission: internal combustion engine, torque converter, and planetary gear set. Based on the developed models, a detailed analysis of the dynamic power train behavior for wide range of operations is carried out. In addition, innovative power train torque estimators based on the engine and torque converter models are designed. The project also includes development of an experimental setup of a power train for the purpose of engine model validation and torque estimator verification.