Jtba John Kessels

Energy management strategies for vehicular electric power systems

In the near future, a significant increase in electric power consumption in vehicles is expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution, and consumption of electric power will be used. Inspired by the research on energy management for hybrid electric vehicles (HEVs), this paper presents an extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments. For this purpose, both off-line optimization methods using knowledge of the driving pattern and on-line implementable ones are developed and tested in a simulation environment. Results show a reduction in fuel use of 2%, even without a prediction of the driving cycle being used. Simultaneously, even larger reductions of the emissions are obtained. The strategies can also be applied to a mild HEV with an integrated starter alternator (ISA), without modifications, or to other types of HEVs with slight changes in the formulation.

Online Energy Management for Hybrid Electric Vehicles

Hybrid electric vehicles (HEVs) are equipped with multiple power sources for improving the efficiency and performance of their power supply system. An energy management (EM) strategy is needed to optimize the internal power flows and satisfy the drivers power demand. To achieve maximum fuel profits from EM, many solution methods have been presented. Optimal solution methods are typically not feasible in an online application due to their computational demand and their need to have a priori knowledge about future vehicle power demand. In this paper, an online EM strategy is presented with the ability to mimic the optimal solution but without using a priori road information. Rather than solving a mathematical optimization problem, the methodology concentrates on a physical explanation about when to produce, consume, and store electric power. This immediately reveals the vehicle characteristics that are important for EM. It is shown that this concept applies to many existing HEVs as well as possible future vehicle configurations. Since the method only focuses on typical vehicle characteristics, the underlying algorithm requires minor computational effort and can be executed in real time. Clear directions for online implementation are given in this paper. A parallel HEV with a 5-kW integrated starter/generator (ISG) is selected to demonstrate the performance of the EM strategy. Simulation results indicate that the proposed EM strategy exhibits similar behavior as an optimal solution obtained from dynamic programming. Profits in fuel economy primarily arise from engine stop/start and energy obtained during regenerative braking. This latter energy is preferably used for pure electric propulsion where the internal combustion engine is switched off.

Energy Management for the Electric Powernet in Vehicles With a Conventional Drivetrain

The electric power demand in road vehicles increases rapidly. Energy management (EM) turns out to be a viable solution for supplying all electric loads efficiently. The EM strategies developed in this paper focus on vehicles with a conventional drivetrain. By exploiting the storage capacity of the battery, the production, and distribution of electric power is rescheduled to more economic moments. In addition, this paper explores the advantages of electric loads with a flexible power demand. Based on optimization techniques, an optimal offline strategy as well as a causal online strategy are presented. Simulations illustrate the benefits of the EM strategies in terms of fuel economy. The online strategy has also been implemented in a series-production vehicle. Real-world experiments on a roller dynamometer test-bench validate the strategy, but also reveal additional fuel benefits due to unexpected side-effects from the engine control unit and the driver. Measured profits in fuel economy are as large as 2.6%, with only minimal changes to the vehicle hardware

Integrated energy & emission management for hybrid electric truck with SCR aftertreatment

Energy management in hybrid vehicles typically relates to the vehicle powertrain, whereas emission management is associated with the combustion engine and aftertreatment system. To achieve maximum performance in fuel economy and regulated pollutants, the concept of (model-based) Integrated Powertrain Control (IPC) is proposed.

Fuel reduction of parallel hybrid electric vehicles

This paper compares the benefits of two parallel drivetrain configurations with an integrated starter generator (ISG): one with the ISG connected directly to the engine, and one with the ISG connected to the drivetrain, after the clutch. Both configurations include start-stop operation, but only the latter one can turn off the engine during propulsion. The effect on fuel economy is analyzed by simulations using optimization over a given driving cycle. Results show that with the latter configuration a much higher fuel reduction can be obtained.

On-line parameter, state-of-charge and aging estimation of Li-ion batteries

This paper presents an on-line model identification method for Li-ion battery parameters that combines high accuracy and low computational complexity. Experimental results show that modeling errors are smaller than 1% throughout the feasible operating range. The identified model is used in a state observer - an Extended Kalman Filter (EKF) - to obtain an indication about the battery State of Charge (SoC). A novel method to estimate the actual battery capacity on-line, based on the data from the state observer is presented. Based on the real battery capacity, an indication about the State of Health (SoH) can be given. Simulation and experimental results are presented to validate the proposed methodology. Battery capacity estimation errors under 4% are achieved by using only 30 minutes of data (battery voltage and current measurements) acquired during normal driving.

Integrated powertrain control for hybrid electric vehicles with electric variable transmission

The electric variable transmission (EVT) offers a powersplit for hybrid electric vehicles by integrating two motor/ generator sets into one electric machine. This double rotor concept implements a continuously variable transmission between the engine and the driveline, including the possibility for electric propulsion. To guarantee good energy efficiency of the overall vehicle configuration, an integrated powertrain control (IPC) strategy is developed. First, optimization of the transmission ratio is analyzed by considering energy losses in the EVT. Next, an energy management strategy is presented incorporating the complete hybrid functionality of the EVT. Simulation results demonstrate feasibility of this IPC strategy and support the design process for optimal component specifications.

Fuel reduction potential of energy management for vehicular electric power systems

In the near future a significant increase in electric power consumption in vehicles is to be expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution and consumption of the electric power can be used. This paper considers a vehicle configuration with a conventional drive train. Two energy management strategies that control the alternator power are analysed: a regenerative braking strategy and a more advanced strategy based on optimisation techniques. The potential behind these strategies is analysed by studying the typical characteristics of components that are directly related to the energy flow in the vehicle. It is shown that operating the internal combustion engine at the highest efficiency will not inherently lead to the lowest fuel consumption. Subsequently, engineering rules are presented to evaluate the performance that can be expected for each strategy. The component characteristics are included as input parameters to make the method generally applicable. To show the value of the engineering rules, the potential fuel reduction is computed for a specific vehicle configuration and driving cycle and compared with simulations results.

Plug-in hybrid electric vehicles in dynamical energy markets

The plug-in hybrid electric vehicle allows vehicle propulsion from multiple internal power sources. Electric energy from the grid can be utilized by means of the plug-in connection. An on-line energy management (EM) strategy is proposed to minimize the costs for taking energy from each power source. Especially in a dynamical energy market, an on-line optimization algorithm is desirable since energy prices change over time. By construction, the proposed EM system can operate with, and without prediction information. If predictions are available, an electronic horizon is applied to anticipate on up-coming events and further optimize the strategy. Illustrative examples are given to explain the added value for both solutions. Also the situation where energy is transferred back to the grid is considered.

Smart vehicle powernet enabling complete vehicle energy management

There is a strong need for energy management in vehicles, because of the significant amount of energy they consume during their lifespan. Owing to the introduction of advanced powertrain configurations like hybrid electric vehicles, the complexity of the supervisory controllers is increasing rapidly. Besides propulsion power, it is also desirable to take the power request from auxiliaries into account, such that “blind” and inefficient operations at (sub) system level are avoided. This vision paper proposes a novel control concept for complete vehicle energy management, maximizing the energy efficiency of the vehicle powernet whereas complexity of the control architecture remains limited. This is achieved by constructing a smart vehicle powernet with programmable auxiliaries which relies on decentralized control. Energy is “traded” between suppliers and consumers according to a price-based control philosophy, taking into account all energy flows in the vehicle. Maximum hardware flexibility is guaranteed because systems take their decisions autonomously. This enables “plug & play” auxiliaries, that can be installed without modifications for the rest of the vehicle or the energy management system. The time required for testing and calibration significantly reduces, whereas global energy efficiency can still be achieved.