Hybrid Electric Vehicles (HEVs) and Plug-In HEVs (PHEVs)

Hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) have attracted considerable attention due to their potential ability to reduce petroleum consumption and greenhouse gas (GHG) emissions. This capability is mainly attributed to the following: 1) the potential for downsizing the engine; 2) the capability of recovering energy during braking, and thus, recharging the energy storage unit (e.g., battery or ultracapacitor); and 3) the ability to minimize engine operation at speeds and loads where fuel efficiency is low. In addition, hybridization, which typically refers to the power requirements for the electric motor or the degree of electrification, of conventional powertrain systems allows elimination of near-idle engine operation, thus enabling direct fuel economy enhancement. A typical HEV (see Fig. 1) consists of the fuel converter (internal combustion engine), the inverter, the battery, and the electric machines (motor and generator). Depending on their architecture, HEVs fall into one of several categories: 1) parallel; 2) series; or 3) power split. In parallel HEVs, both the engine and the motor are connected to the transmission, and thus, they can power the vehicle either separately or in combination. The series HEV, in which the electric motor is the only means of providing the power demanded by the driver, is the simplest HEV configuration. Finally, the power split HEV can operate either as a parallel or a series HEV, combining the advantages of both.

EVs may be also classified based on the degree of hybridization as either 1) micro HEVs, 2) mild HEVs, or 3) full HEVs. In micro HEVs, or start/stop vehicles, the engine is turned off during braking or at stop to avoid idling operation, and the starter motor is used to start the engine when the driver presses the accelerator pedal. A mild HEV is essentially a conventional vehicle with an oversized starter, also allowing the engine to be turned off whenever the car is coasting, braking, or stopped and quickly restart whenever the driver presses the accelerator pedal. The motor is often mounted between the engine and the transmission, substituting for the torque converter, and it can be used to supply additional power when accelerating. Micro and mild HEVs include only some of the features of HEVs and therefore usually achieve only limited fuel savings. In contrast, full HEVs, also called strong HEVs, have larger electric machine and battery. The electric machine (in motor mode) can power the vehicle separately if necessary and regenerate energy (in generator mode) from braking and store it in the battery.

Depending on the driving mode, e.g., cruising or braking, either a positive or a negative torque is demanded from the powertrain. The power available from the electric machine is regulated by adjusting its torque such that it can be either positive or negative depending on the operating mode. In the motor mode, the electric machine contributes power to the driveline by drawing electrical energy from the battery. In the generator mode, the electric machine absorbs power from the driveline and charges the battery. In cruising, the power demanded from the powertrain is expressed by a positive amount of torque, given a fixed engine speed. In braking, the power is expressed by a negative torque. The generator absorbs the maximum possible amount as determined by the system’s physical constraints. If residual braking energy remains, the friction brakes handle this. For the next 20–30 years, the gasoline HEV offers a promising path to cost-effective reduction in fuel use. Relative to conventional spark-ignition and diesel engines, gasoline HEVs are projected to offer increasing efficiency gains and a narrowing price premium.

The power management control algorithm in HEVs and PHEVs determines how to split the power demanded by the driver between the thermal and electrical subsystems so that maximum fuel economy and minimum pollutant emissions can be achieved. Developing the control algorithm in HEVs and PHEVs constitutes a challenging control problem and has been the object of intense study for the last 20 years.

Relevant Publications:

  1. Malikopoulos, A.A., “A Multiobjective Optimization Framework for Online Stochastic Optimal Control in Hybrid Electric Vehicles,” IEEE Trans. on Control Systems Tech., Vol. 24, 2, pp. 440-450, 2016 (pdf).
  2. Shaltout, M., Malikopoulos, A.A., Pannala, S., and Chen, D., “A Consumer-Oriented Control Framework for Performance Analysis in Hybrid Electric Vehicles,” IEEE Trans. on Control Systems Tech., 23, 4, pp. 1451-1464, 2015 (pdf).
  3. Malikopoulos, A.A., “Supervisory Power Management Control for Hybrid Electric Vehicles: A Survey,” IEEE Trans. Intell. Transp. Syst., 15, 5, pp. 1869-1885, 2014 (pdf).
  4. Malikopoulos, A.A., “Impact of Component Sizing in Plug-In Hybrid Electric Vehicles for Energy Resource and Greenhouse Emissions Reduction,” Energy Resour. Technol., 135, 4, pp. 041201-9, 2013 (pdf).
  5. Park, S., Malikopoulos, A.A., Kokkolaras, M., and Jung, D., “Thermal Management System Modeling and Component Sizing for Heavy Duty Series Hybrid Electric Vehicles,” J. Heavy Vehicle Systems, Vol. 18, 3, pp.272–287, 2011 (link).
  6. Malikopoulos, A.A., “Pareto Efficient Policy for Supervisory Power Management Control,” in Proceedings of 2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2443-2448, 2015 (pdf).
  7. Pourazarm, S., Cassandras, C.G., and Malikopoulos, A.A., “Optimal Routing of Electric Vehicles in Networks with Charging Nodes: A Dynamic Programming Approach,” Proceedings of the IEEE International Electric Vehicle Conference, 2014 (pdf).
  8. Shaltout, M., Malikopoulos, A.A., Pannala, S., and Chen, D., “Multi-Disciplinary Decision Making and Optimization for Hybrid Electric Propulsion Systems,” Proceedings of the IEEE International Electric Vehicle Conference, 2014.
  9. Malikopoulos, A.A.“Online Identification of Power Required for Self-Sustainability of the Battery in Hybrid Electric Vehicles,” Proceedings of the 2014 Technical Conference of the ASME Internal Combustion Engine Division, Columbus, Indiana, Oct 19-22, ICEF2014-5401, 2014 (pdf).
  10. Malikopoulos, A.A., “Stochastic Optimal Control for Series Hybrid Electric Vehicles,” Proceedings of 2013 American Control Conference, 1191-1196, 2013 (pdf).
  11. Malikopoulos, A.A. and Smith, D.E., “An Optimization Model for Plug-in Hybrid Electric Vehicles,” Proceedings of the 2011 Technical Conference of the ASME Internal Combustion Engine Division, ICEF2011-60028, 2011 (pdf).