Ongoing:

• Ivan Ruškan, 2024-, Supervisor: Prof. Joško Deur, Thesis connected with project Design of autonomous vehicle active seat suspension mechatronic system (DAVAS).
• Lea Pavelko, 2021-, Supervisor: Prof. Joško Deur, Thesis connected with project Safe Speed Anticipating for Encountering Pedestrian Crossing.

Completed:

• Jure Soldo, 2020-2023, Supervisor: Prof. Joško Deur, Thesis connected with project Adaptive and Predictive Control of Plug-in Hybrid Electric Vehicles (ACHIEVE).
• Ivan Cvok, 2018-2022, Supervisor: Prof. Joško Deur, Thesis connected with project Qualifying and Implementing a User-centric Designed and Efficient Electric Vehicle (QUIET).
• Vanja Ranogajec, 2015-2019, Supervisor: Prof. Joško Deur, 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.
• Experimental Characterization of Electric Scooter Li-Ion Battery Pack Aging, J. Deur, 2019.
• 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.
• Conducting optimization of motor torque and clutch states to balance energy savings with component durability.
• Developing and evaluating rule-based and model predictive control strategies against dynamic programming-optimized benchmarks for energy efficiency.

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:

• Modeling of pedestrian behavior during interaction with vehicle at crosswalks
• Deriving prediction model of pedestrian behaviour at crosswalks
• Design of control system providing safe and effective interaction with pedestrians
• Development of safety manifold to ensure robustness w.r.t. prediction model errors

The goal of the project is commercialization of the inovation in the field of contactless measurement of a dry clutch temperature, developed at FER in the project „System for telemetric temperature measurement for rotational drivetrain elements“, conducted under the Proof-of-Concept (PoC-5) programme. Moreover, activities will encompass drafting a licence agreement, and production of 20 demo RotoTemp measurement systems, in order to present innovation to potential partners/licensors to assess their reaction and interest. The expected project outcomes are the following: patent protection according to the elaborated commercialization strategy, prepared draft of commercialization/licensing agreement, produced 20 demo RotoTemp measurement systems, that are presented and given without charge as samples to potential key partners. The best case scenario outcome will be signing commercialization/licensing agreement with partner(s) during the project. 

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:

• Modelling, simulation, and optimisation processes;
• On-line optimal control, estimation, and prediction;
• Strategic planning; and
• 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 unknown driving conditions.

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: The introduction of vehicle dynamics control systems (ABS, TCS, ESP, ARC, CDC, etc.) leads to substantial improvements in vehicle safety during critical maneuvers, ride comfort, and handling performance. Commercial solutions of these systems are based on traditional ABS hydraulic-brake actuators. The development and application of new actuators, such as active steering, active differential, and active suspension, have intensified research activities aimed at further improving vehicle dynamics control performance. Control systems require 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 controllers and estimators relies heavily on mathematical models of vehicle dynamics. These models need to have a simple structure that faithfully describes basic vehicle dynamics modes.

The aims of the proposed research are:

• Development of precise control-oriented vehicle dynamics models with an emphasis on tire models;
• Development of vehicle dynamics estimators based on the so-called sensor fusion concept (fusion of ABS sensors, accelerometers, gyroscopes, and GPS);
• Design and comparative analysis of vehicle dynamics control systems for various configurations of actuators and sensors.

The project aims to provide clear answers about the level of improvements in driving safety, comfort, and performance based on the application of advanced actuators and sensors, as well as the optimal structures of estimators and controllers required to achieve these improvements. The final research results would include faithful nonlinear and linearized models of tire and vehicle dynamics and optimal systems for vehicle dynamics estimation and control for various tasks.

The proposed models, estimators, and controllers are planned to be verified through computer simulations and experimental methods. The experimental verification will be carried out using the Faculty's existing test vehicle, which features an in-wheel electrical servo-motor. Depending on the available financial resources, the vehicle could be upgraded with a direct drive for steering and several advanced tire and vehicle dynamics sensors.

The research results could have direct applications in the automotive industry, as well as in the railway vehicle and broader transportation industries. The research is expected to contribute to global efforts to increase transportation safety.

Project number: 120-0361621-1896

Period: January 2007 - 2012

Summary: Hybrid vehicle drive has generally been accepted as an effective solution for improving vehicle energy consumption and reducing environmental pollution, which are two key issues in modern transportation. At the same time, it is necessary to meet the opposing expectations of vehicle users for good performance, comfort, safety, and driving range. Hybrid vehicles are powered by multiple types of power sources. Electric hybrids consist of an internal combustion engine (ICE) and an electric motor/generator (or an additional separate generator) and energy storage media such as chemical batteries and/or ultracapacitors. This allows for energy savings and reduced emissions by utilizing kinetic energy during braking, operating the ICE in a fuel-efficient range, and potentially reducing the size of the ICE, while maintaining good performance and the long range of conventionally powered vehicles.

An alternative to electric hybrids, which could offer greater energy efficiency, is hydraulic hybrids. Instead of an electric motor/generator and batteries, they use a hydraulic unit (motor/pump) and a hydropneumatic accumulator.

The key challenges of hybrid vehicles are:

• Finding the optimal combination of hybrid drive elements,
• Developing an appropriate energy management strategy for multiple power sources.

The main outcomes of the proposed project will be mathematical models of hybrid drives, which will serve as the foundation for high-quality analysis and synthesis of hybrid vehicle control, as well as methods for optimal control of hybrid vehicles. To experimentally verify the mathematical models and control methods, an experimental hybrid vehicle and a small experimental hydraulic drive will be constructed. Additionally, a comparative analysis of hydraulic and electric hybrid drives will be conducted, along with research into automotive mechatronic subsystems, with a focus on their applications in hybrid vehicles.

The proposed research aims to acquire expert knowledge to contribute to current global research in the field of hybrid vehicles, which is evidently the future of automotive technology. It is also crucial to disseminate knowledge about hybrid vehicles and automotive mechatronics to interested parties in the domestic environment (young researchers, students, scientists, experts). Furthermore, the project is expected to expand existing collaborations with the global automotive industry and provide support to domestic science and industry on related issues.

Project number:

Period: 2007 - 2011

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

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

Experimental analysis is the only way to obtain reliable information about friction coefficients and forces. Special machines—tribometers—are typically used for this purpose. In most cases, tribometers are oriented toward static friction analysis, where the general conditions of friction remain unchanged during testing. However, dynamic and variable conditions can also be of particular interest, such as when normal force or relative velocity changes rapidly, or in the study of other transient friction phenomena like hysteresis or the Stribeck effect.

For such experiments and testing procedures, this project proposes the development of a numerically controlled machine for friction analysis, characterized by very fast dynamics, high accuracy, versatility, and automation of measuring procedures. These features will be made possible by fast servo-drives, precise measuring equipment, the ability to change sliding pairs, and specifically developed control algorithms and measurement procedures.

Project number: 0120-053

Period: June 2002 -

Summary: The application of various control systems in vehicles results in significant improvements in 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 powertrain quantities that cannot be conveniently measured, it is necessary to develop on-line estimators of these quantities.

In known models of automotive elements and systems, some important dynamic 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). This project proposes the development of simple, physical, control-oriented, and experimentally validated dynamic models of automotive powertrains. Alternatively, the application of black-box models based on neural networks is also considered. The emphasis is on modeling the internal combustion engine, electronic throttle body, wet clutch of an automatic transmission, and tires. A detailed analysis of the dynamic behavior of these elements and the overall powertrain with automatic transmission is conducted to facilitate model parameterization and control system design.

Estimation of engine torque, vehicle traction force, and other quantities of an automotive powertrain is usually conducted in an open loop. This project proposes the development and experimental verification of closed-loop nonlinear estimators to increase the static and dynamic accuracy of estimation in the presence of significant process parameter variations. Special attention is given to the choice of estimator structure to ensure estimator robustness across a wide operating range.

Based on the developed models and estimators, various high-performance automotive control systems are designed and experimentally tested. The emphasis is on idle speed control of the gasoline engine, active compensation of torque pulses in hybrid vehicles, servo control of the 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 powertrains are necessary for the development of different automotive control systems. The project includes improvements and extensions of dynamic models of basic elements of powertrains with automatic transmission: internal combustion engine, torque converter, and planetary gear set. Based on the developed models, a detailed analysis of the dynamic powertrain behavior across a wide range of operations is carried out. In addition, innovative powertrain torque estimators based on the engine and torque converter models are designed. The project also includes the development of an experimental setup of a powertrain for the purpose of engine model validation and torque estimator verification.