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Eindhoven, Netherlands

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. Source


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. Source


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. Source


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. Source


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. Source

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