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Ngo D.V.,TU Eindhoven | Hofman T.,TU Eindhoven | Steinbuch M.,TU Eindhoven | Serrarens A.F.A.,Drivetrain Innovations B V
Proceedings of the American Control Conference | Year: 2011

The definition of a performance index for the optimization design and optimal control problem of a Hybrid Electric Vehicle is not often considered and analyzed explicitly. In literature, there is no study about proposing a method of building or evaluating whether a performance index is appropriate. In this paper a method of objectively analyzing the performance index for the optimal control problem of a parallel Hybrid Electric Vehicle is introduced. The correlations and interdependencies among the objectives of the performance index are addressed by using the Singular Value Decomposition method. It is found that a simplified performance index consisting of fuel consumption and comfort can be obtained without sacrificing the vehicle performance compared to the case with the original one including fuel consumption, comfort and driveability. © 2011 AACC American Automatic Control Council.


Ngo V.D.,TU Eindhoven | Colin Navarrete J.A.,TU Eindhoven | Hofman T.,TU Eindhoven | Steinbuch M.,TU Eindhoven | Serrarens A.,Drivetrain Innovations B V
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering | Year: 2013

This paper aims at designing optimal gear shift strategies for conventional passenger vehicles equipped with discrete ratio transmissions. In order to study quantitatively an optimal trade-off between the fuel economy and the driveability, the vehicle driveability is addressed in a fuel-optimal gear shift algorithm based on dynamic programming by three methods: method 1, weighted inverse of power reserve; method 2, constant power reserve; method 3, variable power reserve. Furthermore, another method based on stochastic dynamic programming is proposed to derive an optimal gear shift strategy over a number of driving cycles in an average sense, hence taking into account the vehicle driveability. In contrast with the dynamic-programming-based strategy, the obtained gear shift strategy based on stochastic dynamic programming is real time implementable. A comparative analysis of all proposed gear shift methods is given in terms of the improvements in the fuel economy and the driveability. The variable-power-reserve method achieves the highest fuel economy without sacrificing the driveability. © IMechE 2013.


Ngo V.,TU Eindhoven | Hofman T.,TU Eindhoven | Steinbuch M.,TU Eindhoven | Serrarens A.,Drivetrain Innovations B V
IEEE Transactions on Vehicular Technology | Year: 2012

This paper proposes a design method for the energy management strategy to explore the potential fuel saving of a hybrid electric vehicle (HEV) equipped with an automated manual transmission. The control algorithm is developed based on the combination of dynamic programming (DP) and Pontryagin's minimum principle (PMP) to optimally control the discrete gearshift command, in addition to the continuous power split between the internal combustion engine and the electric machine. The proposed method outperforms DP in terms of computational efficiency, being 171 times faster, without loss of accuracy. Simulation results for a middle-sized HEV on the New European Drive Cycle show that, to further optimize the gearshift strategy, an additional fuel saving of 20.3% can be reached. Furthermore, with the start-stop functionality available, it is shown that the two-point boundary-value problem following from PMP cannot be solved with sufficient accuracy without loss of optimality. This means that the finding of a constant value for the Lagrange multiplier while satisfying the battery state-of-energy (SOE) at the terminal time is not always guaranteed. Therefore, an alternative approach of SOE feedback control to adapt the Lagrange multiplier is adopted. The obtained results are very close to the globally optimal solution from DP. Simulation results, including the start-stop functionality, show that the relative fuel saving can be up to 26.8% compared with the case of a standard gearshift strategy. © 2012 IEEE.


Van Berkel K.,TU Eindhoven | Hofman T.,TU Eindhoven | Vroemen B.,Drivetrain Innovations B V | Steinbuch M.,TU Eindhoven
IEEE Transactions on Vehicular Technology | Year: 2012

This paper presents the design of an optimal energy management strategy (EMS) for a low-cost mechanical hybrid powertrain. It uses mechanical components only-a flywheel, clutches, gears, and a continuously variable transmission-for its hybrid functionalities of brake energy recuperation, reduction of inefficient part-load operation of the engine, and engine shutoff during vehicle standstill. This powertrain has mechanical characteristics, such as a relatively small energy storage capacity in the form of the compact flywheel and multiple driving modes to operate the powertrain because of the use of clutches. The optimization problem is complex because it is twofold: 1) to find the optimal sequence of driving modes and 2) to find the optimal power distribution between the engine, the flywheel, and the vehicle. Dynamic programming is used to compute the globally optimal EMS for six representative driving cycles. The main design criterion is the minimization of the overall fuel consumption, subject to the system's kinematics, dynamics, and constraints. The results provide a benchmark of the fuel-saving potential of this powertrain design and give insight into the optimal utilization of the flywheel system. In addition, the complexity (and computation time) of the problem is reduced by a priori (static) optimization of the power distribution for each driving mode. Static optimization of a dynamic optimization problem yields a suboptimal solution; however, the results show that the consequences on the fuel saving are small with respect to the optimal one (the difference is < 0.8%). © 2012 IEEE.


Van Berkel K.,TU Eindhoven | Veldpaus F.,TU Eindhoven | Hofman T.,TU Eindhoven | Vroemen B.,Drivetrain Innovations B V | Steinbuch M.,TU Eindhoven
IEEE Transactions on Control Systems Technology | Year: 2014

Automatically controlled clutches are widely used in advanced automotive powertrains to transmit a demanded torque while synchronizing the rotational speeds of the shafts. The two objectives of the clutch engagement controller are a fast clutch engagement to reduce the frictional losses and thermal load, and a smooth clutch engagement to accurately track the demanded torque without a noticeable torque dip. Meanwhile, the controller is subjected to standard constraints such as model uncertainty and limited sensor information. This paper presents a new controller design that explicitly separates the control laws for each objective by introducing three clutch engagement phases. The time instants to switch between the subsequent phases are chosen such that the desired slip acceleration is achieved at the time of clutch engagement. The latter can be interpreted as a single calibration parameter that determines the tradeoff between fast and smooth clutch engagement. The controller is elaborated for a mechanical hybrid powertrain that uses a flywheel as a secondary power source and a continuously variable transmission. Simulations and experiments on a test rig show that the control objectives are realized with a robust and relatively simple controller. © 2013 IEEE.


Ngo V.D.,TU Eindhoven | Hofman T.,TU Eindhoven | Steinbuch M.,TU Eindhoven | Serrarens A.,Drivetrain Innovations B V
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering | Year: 2014

In this paper, a design methodology is developed to condtruct the gear shift map for the automotive transmissions used in conventional and hybrid electric vehicles. The methodology utilizes an optimal gear shift strategy to derive the optimal gear shift patterns over a wide range of driving profiles. Then, statistical theory is applied to analyse the obtained gear shift patterns for a gear shift map. The designed gear shift map improves the fuel economy and driveability. It is consistent, robust to shift busyness and real-time implementable. The design process is flexible and time efficient such that applicability to various powertrain systems configured with discrete-ratio transmissions is possible. Validation on a test vehicle proves the effectiveness of the design methodology. © IMechE 2013.


Van Berkel K.,TU Eindhoven | Klemm W.,FEV | Hofman T.,TU Eindhoven | Vroemen B.,Drivetrain Innovations B V | Steinbuch M.,TU Eindhoven
2013 European Control Conference, ECC 2013 | Year: 2013

This paper presents the design of an optimal Energy Management Strategy (EMS) for a hybrid vehicle that starts with a cold powertrain. The cold start negatively affects the combustion and transmission efficiency of the powertrain, caused by the higher frictional losses due to increased hydrodynamic viscosity effects. The excess fuel consumption of the engine and the excess power loss of the transmission are modeled by static relations as a function of the lubrication oil temperature. The thermodynamics in the powertrain during the heating period of the powertrain is approximated by a first-order dynamic model. The main design criterion for the optimal EMS is the minimization of the overall fuel consumption over a pre-defined driving cycle. Dynamic programming is used to find the globally optimal solution for six representative driving cycles. The results show that the cold start has a significant impact on the fuel consumption of the hybrid vehicle, yet its influence on the optimal EMS is negligible. © 2013 EUCA.


van Keulen T.,TU Eindhoven | de Jager B.,TU Eindhoven | Serrarens A.,TU Eindhoven | Serrarens A.,Drivetrain Innovations B V | Steinbuch M.,TU Eindhoven
Oil and Gas Science and Technology | Year: 2010

To benchmark a hybrid vehicle's Energy Management Strategy (EMS) usually a given, often certified, velocity trajectory is exploited. In this paper it is reasoned that it is also beneficial to optimize the velocity trajectory. Especially optimizing the vehicle braking trajectories, through maximization of energy recuperation, results in considerable fuel savings on the same traveled distance. Given future route (target velocities as function of traveled distance/location), traffic, and possibly weather information, together with the vehicle's road load parameters, the future power request trajectory can be estimated. Dynamic Programming (DP) techniques can then be used to predict the optimal power split trajectory for the upcoming route, such that a desired state-of-charge at the end of the route is reached. The DP solution is re-calculated at a certain rate in order to adapt to changing conditions, e.g., traffic conditions, and used in a lower level real-time EMS to guarantee both battery state-of-charge as well as minimal fuel consumption. © 2009, Institut français du pétrole.


Van Berkel K.,TU Eindhoven | Hofman T.,TU Eindhoven | Vroemen B.,Drivetrain Innovations B V | Steinbuch M.,TU Eindhoven
Proceedings of the American Control Conference | Year: 2011

This paper presents the modeling and design of an optimal Energy Management Strategy (EMS) for a flywheel-based hybrid vehicle, that does not use any electrical motor/generator, or a battery, for its hybrid functionalities. The hybrid drive train consists of only low-cost components, such as a flywheel module and a continuously variable transmission. This hybrid drive train is characterized by a relatively small energy capacity (flywheel) and discrete shifts between operation modes, due to the use of clutches. The main design criterion of the optimized EMS is the minimization of the overall fuel consumption, over a pre-defined driving cycle. In addition, comfort criteria are formulated as constraints, e.g., to avoid high-frequent shifting between driving modes. The criteria are used to find the optimal sequence of driving modes and the generated engine torque. Simulations show a fuel saving potential of 20% to 39%, dependent on the chosen driving cycle. © 2011 AACC American Automatic Control Council.


Ngo D.V.,TU Eindhoven | Hofman T.,TU Eindhoven | Steinbuch M.,TU Eindhoven | Serrarens A.F.A.,Drivetrain Innovations B V
Proceedings of the 2010 American Control Conference, ACC 2010 | Year: 2010

Control strategies for Hybrid Electric Vehicles (HEVs) are generally aimed at optimally choosing the power distribution between the internal combustion engine and the electric motor in order to minimize the fuel consumption and/or emissions. Using vehicle navigation systems in combination with Global Positioning Systems and Geographical Information Systems allow further optimization of the power distribution by utilizing the route information. In this paper, a new control algorithm based on a combination of dynamic programming and classical optimal control theory is proposed for the Energy Management System in parallel HEVs to improve the fuel economy over a preview route segment. The proposed algorithm optimizes not only the gear position and the engine power yet also the vehicle velocity. The vehicle is controlled to complete this route segment in a predefined time length. Using this method more than 11% fuel saving is computed on an optimized cycle compared to a standard city cycle with equal time length and average speed. © 2010 AACC.

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