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Optimal Control of a Mechanical Hybrid Powertrain

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 two fold: 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 systems 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%).

Multiobjective control: an overview

An overview of a number of approaches to the multiobjective control problem is given. In practice, this problem usually boils down to a mixed-norm optimization, where traditionally the norms of interest are H/sub 2/, H/sub /spl infin// and l/sub 1/. To capture different, often conflicting, design specifications a single-norm form is usually not enough and therefore a mixed-norm formalism combining these norms would be of considerable interest. Although it would be nice to have all three norms present, most approaches focus on the two-norm problem. Frequently encountered is the H/sub 2//H/sub /spl infin// mixed-norm optimization problem, but combinations of l/sub 1/ and the other two norms are starting to get more attention. It will be seen that the solution to the mixed-norm optimization problem has not yet reached a final shape, since most methods still exhibit problems, like not being able to find a solution if performance specifications are tight, or generating high-order or too conservative controllers, etc.

Control of a hydraulically actuated continuously variable transmission

Vehicular drivelines with hierarchical powertrain control require good component controller tracking, enabling the main controller to reach the desired goals. This paper focuses on the development of a transmission ratio controller for a hydraulically actuated metal push-belt continuously variable transmission (CVT), using models for the mechanical and the hydraulic part of the CVT. The controller consists of an anti-windup PID feedback part with linearizing weighting and a setpoint feedforward. Physical constraints on the system, especially with respect to the hydraulic pressures, are accounted for using a feedforward part to eliminate their undesired effects on the ratio. The total ratio controller guarantees that one clamping pressure setpoint is minimal, avoiding belt slip, while the other is raised above the minimum level to enable shifting. This approach has potential for improving the efficiency of the CVT, compared to non-model based ratio controllers. Vehicle experiments show that adequate tracking is obtained together with good robustness against actuator saturation. The largest deviations from the ratio setpoint are caused by actuator pressure saturation. It is further revealed that all feedforward and compensator terms in the controller have a beneficial effect on minimizing the tracking error.

Fast and Smooth Clutch Engagement Control for a Mechanical Hybrid Powertrain

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.

Hierarchical control of the Zero Inertia powertrain

Abstract A vehicular powertrain incorporating a continuously variable transmission (CVT) and a flywheel is considered and divided into a number of system layers with descending response times. Among these layers are the electronic circuits supplying the control currents, solenoids controlling the CVT pulley pressures, the engine throttle valve, the CVT, the engine, and finally the vehicle. Figure 2 in Section 1 will illustrate the system layers and their interaction in more detail. In view of the system layer hierarchy, a hierarchical—or cascaded—control scheme is introduced, simplifying the total control design. Such an approach is justified if the operation of each layer can be described independently of the rest of the system, i.e., the faster layer can be assumed static with respect to the slower one (Singular Perturbation Methods in Control: Analysis and Design, Academic Press, New York, 1986, p. 1). This assumption does not appear to be appropriate for all layers, though not insurmountable in practice. The new Zero Inertia powertrain, control hierarchy and the results from simulations and various experiments are discussed in the paper.

Optimal Control of a Mechanical Hybrid Powertrain With Cold-Start Conditions

This paper investigates the impact of cold-start conditions on the fuel-saving potential and the associated optimal energy controller of a mechanical hybrid powertrain. The mechanical hybrid powertrain uses a flywheel system to add fuel-saving functionalities to a conventional powertrain, which consists of an internal combustion engine and a continuously variable transmission (CVT). The cold-start conditions refer to a low powertrain temperature, which increases the frictional power dissipation in the engine and transmission, and a stationary (or energyless) flywheel system, which must be energized to a minimum energy level before it can be effectively utilized. The heating of the powertrain and the initialization of the flywheel system can be influenced by the energy controller, which controls the power distribution between the engine, the flywheel, and the vehicle. The energy controller aims at minimizing the overall fuel consumption for a given driving cycle. The optimal energy controller is found analytically for a simplified model to gain qualitative insights in the controller and numerically using dynamic programming for a detailed model to quantify the impact on the fuel consumption. The results show that the cold-start conditions have a significant impact on the fuel-saving potential, yet a negligible impact on the optimal energy controller. The latter result implies that the temperature state can be eliminated from the state space of the energy controller, which is an important step toward the design of an effective yet simple energy controller suitable for real-time implementation.

From Optimal to Real-Time Control of a Mechanical Hybrid Powertrain

This brief presents the design of an energy controller for a mechanical hybrid powertrain, which is suitable for implementation in real-time hardware. The mechanical hybrid powertrain uses a compact flywheel module to add hybrid functionalities to a conventional powertrain that consists of an internal combustion engine and a continuously variable transmission. The control objective is to minimize the overall fuel consumption for a given driving cycle. The design approach follows a generic framework to: 1) solve the optimization problem using optimal control; 2) make the optimal controller causal using a prediction of the future driving conditions; and 3) make the causal controller robust by tuning of one key calibration parameter. The highly constrained optimization problem is solved with dynamic programming. The future driving conditions are predicted using a model that smoothly approximates statistical data, and implemented in the receding model predictive control framework. The controller is made tunable by rule extraction from the model predictive controller, based on physical understanding of the system. The resulting real-time controller is transparent, causal, and robust, where the latter is shown by simulations for various driving cycles and start conditions.

Control of a continuously variable transmission in an experimental vehicle

Abstract This paper focusses on the development of a component controller for a hydraulically actuated metal push-belt Continuously Variable Transmission (CVT), using models for the mechanical and the hydraulic part of the CVT. The ratio controller guarantees that one clamping pressure setpoint is minimal, while the other is raised above the minimum level to enable shifting. This approach is beneficial with respect to efficiency and wear. Vehicle experiments show that good tracking is obtained. The largest deviations from the ratio setpoint are caused by hardware limitations.

Topology and Flywheel Size Optimization for Mechanical Hybrid Powertrains

Mechanical hybrid powertrains have the potential to improve the fuel economy of passenger vehicles at a relatively low cost, by adding a flywheel and only mechanical transmission components to a conventional powertrain. This paper presents a systematic approach to optimizing the topology and flywheel size, which are the key design parameters of a mechanical hybrid powertrain. The topology is optimized from a limited set of over 20 existing mechanical hybrid powertrains described in the literature. After a systematic classification of the topologies, a set of four competitive powertrains is selected for further investigation. The fuel-saving potential of each hybrid powertrain is computed using an optimal energy controller and modular component models, for various flywheel sizes and for three certified driving cycles. The hybridization cost is estimated based on the type and size of the components. Other criteria, such as control complexity, clutch wear, and driving comfort are qualitatively evaluated to put the fuel-saving potential and the hybridization cost into a wider perspective. Results show that, for each of the four investigated hybrid powertrains, the fuel-saving benefit returns the hybridization investment well within (about 50%) the service life of passenger vehicles. The optimal topology follows from a discussion that considers all the optimization criteria. The associated optimal flywheel size has an energy storage capacity that is approximately equivalent to the kinetic energy of the vehicle during urban driving (50 km/h).

Analysis of optimal mechanical-hybrid powertrain topologies

This study presents an overview of mechanical-hybrid vehicle concepts found in the literature, and compares the fuel saving potential and the estimated cost of a selection of four competitive powertrain topologies. To make a fair comparison, the fuel saving of each concept is computed using the same reference vehicle, a selection of the same set of components, the same driving cycles, and an optimal energy management strategy. The flywheel size is left as a design parameter. Dynamic programming is used to find the optimal energy management strategy, by minimizing the fuel consumption of a given hybrid powertrain model for a given driving cycle. The production cost is estimated using weight-specific parameters, so that components such as the flywheel size can be scaled. Results show that these competitive topologies represent different trade-offs between fuel saving, cost, and control complexity. In general, the investment of the additional mechanical-hybrid components is returned after approximately 50,000 km, which is makes it a very competitive technology.