Predictive control of drive systems

In order to counteract global warming, it is necessary to reduce the emissions of greenhouse gases and thus the consumption of fossil fuels as quickly as possible. The need for energy-saving solutions is further reinforced by rising energy costs.

In the mobility sector, these goals are being pursued through increasing electrification of the powertrain. This includes not only the switch to battery electric vehicles but also the use of fuel cell vehicles and the hybridization of vehicles with internal combustion engines. However, the mere presence of electric components in the powertrain is not enough - what matters is the optimal interaction of the components. For example, when driving a hybrid vehicle in mountainous terrain, the control concept should ensure that the battery's state of charge is low before a long downhill section. This ensures that the braking energy can then be used to charge the battery.  This is where predictive systems come into play, based for example on information from planned routes, vehicle-to-vehicle communication (V2V) or vehicle-to-infrastructure communication (V2I), which form the basis for optimal control of the vehicle components.

Schematic of a stationary electric vehicle optimally supplied with power by a control system

Fuel cell vehicles

Especially in the heavy-duty vehicle sector, where high performance and long driving ranges are required, the fuel cell is a promising alternative to the internal combustion engine. However, passenger cars can also benefit from this propulsion system due to fast refueling and low weight. To reduce the dynamic stress on the fuel cell, fuel cell vehicles are usually hybrid vehicles, i.e. they also have a battery. This results in the requirement for optimal energy management aiming at an efficient load distribution between the fuel cell and the battery. In addition, sufficient cooling of both power sources is a challenge, especially for heavy-duty vehicles, which calls for efficient thermal management. Regarding both topics, the application of sophisticated predictive strategies allows to increase the efficiency and to prevent component degradation.

Increasing the Efficiency of Conventional Powertrains

The greatest potential to meet short-term emission limits lies in the electrification of conventionally powered vehicles. This is not limited to expanding the powertrain with an electric motor. For example, e-turbos or electrically heatable catalytic converters allow efficiency increases or emission reductions, provided they are efficiently controlled. This requires again predictive information and sophisticated control concepts.

Publications

Ferrara, Alessandro, Stefan Jakubek, and Christoph Hametner. "Energy management of heavy-duty fuel cell vehicles in real-world driving scenarios: Robust design of strategies to maximize the hydrogen economy and system lifetime, opens an external URL in a new window." Energy Conversion and Management 232 (2021): 113795.

Ferrara, Alessandro, and Christoph Hametner. "Impact of Energy Management Strategies on Hydrogen Consumption and Start-up/Shut-down Cycles in Fuel Cell-Ultracapacitor-Battery Vehicles, opens an external URL in a new window." IEEE Transactions on Vehicular Technology (2021).

Zendegan, Saeid, Alessandro Ferrara, Stefan Jakubek, and Christoph Hametner. "Predictive Battery State of Charge Reference Generation Using Basic Route Information for Optimal Energy Management of Heavy-Duty Fuel Cell Vehicles, opens an external URL in a new window." IEEE Transactions on Vehicular Technology 70, no. 12 (2021): 12517-12528.

Vrlić, Martin, Daniel Ritzberger, and Stefan Jakubek. "Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data, opens an external URL in a new window." Energies 13, no. 20 (2020): 5353.

Vrlić, Martin, Daniel Ritzberger, and Stefan Jakubek. "Efficient and life preserving power tracking control of a proton exchange membrane fuel cell using model predictive control, opens an external URL in a new window." In 2020 SICE International Symposium on Control Systems (SICE ISCS), pp. 77-84. IEEE, 2020.

Vrlić, Martin, Daniel Ritzberger, and Stefan Jakubek. "Model-predictive-control-based reference governor for fuel cells in automotive application compared with performance from a real vehicle, opens an external URL in a new window." Energies 14, no. 8 (2021): 2206.

Vrlić, Martin, and Stefan Jakubek. "Degradation Avoiding Start Up and Shut Down of Fuel Cell Stacks for Automotive Application Using Two Plant Model Predictive Control, opens an external URL in a new window." In 2021 6th International Conference on Smart and Sustainable Technologies (SpliTech), pp. 1-6. IEEE, 2021.

Contact

Associate Prof. Dipl.-Ing. Dr.techn. Christoph Hametner

Send email to Christoph Hametner