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This paper develops a new computational approach for energy management in a hydraulic hybrid vehicle. The developed algorithm, called approximate stochastic differential dynamic programming (ASDDP) is a variant of the classic differential dynamic programming algorithm. The simulation results are discussed for two Environmental Protection Agency drive cycles and one real world cycle based on collected data. Flexibility of the ASDDP algorithm is demonstrated as real-time driver behavior learning, and forecasted road grade information are incorporated into the control setup. Real-time potential of ASDDP is evaluated in a hardware-in-the-loop (HIL) experimental setup. [ABSTRACT FROM AUTHOR]

The problem of achieving maximum system efficiency through near-optimal supervisory control (or system power management) in mobile off-highway machines is a theoretically challenging problem. It has been tackled for the first time in this work for displacement-controlled (DC) hydraulic hybrid multi-actuator machines such as excavators, through a two-part publication. In Part I, the theoretical aspects of this problem were outlined, supported by simulations of the theoretically optimal supervisory control (relying on dynamic programming) as well as a novel, implementable rule-based supervisory control strategy(designed to replicate theoretically optimal results). In Part II of the publication, the world's first prototype hydraulic hybrid excavator using throttle-less DC actuation is described, together with machine implementation of the novel supervisory control strategy proposed in Part I. The design choice, or set of component sizes implemented on the prototype, was driven by an optimal sizing study that was previously done. Measurement results from implementation of two different supervisory control strategies are also presented and discussed--the first, a conservative, suboptimal strategy that commanded a constant engine speed and proved that drastic engine downsizing can be performed in excavator and similar applications. The second strategy implemented was the novel, nearoptimal rule-based strategy (or the "minimum-speed" strategy) proposed in Part I that exploited all available system degrees-of-freedom, by commanding the minimum-required engine speeds (to meet DC actuator flow requirements) at every instant in time. While the actual engine was not downsized on the prototype excavator, both the single-point and minimum-speed strategies showed that for the aggressive, digging cycles that such machines are typically used for, the DC hydraulic hybrid architecture enables engine operation at or near 50% of maximum engine power without loss of productivity. As described in Part I. actually downsizing the engine by 50% with use of the near-optimal, minimum speed strategy will enable significant gains in efficiency (in terms of grams of fuel consumed) over standard valve-controlled architectures (55%) as well as DC nonhybrid architectures (25%) in cyclical operation. [ABSTRACT FROM AUTHOR]

Recent demands on improved system efficiency and reduced system emissions have driven improvements in hydraulic system architectures as well as system supervisory control strategies employed in mobile multi-actuator machinery. Valve-controlled (VC) architectures have been in use for several decades and have seen moderate improvements in terms of system efficiency. Further, throttle-less concepts such as displacementcontrolled (DC) actuation have been recently proposed and successfully demonstrated efficiency improvements in numerous prototypes (wheel-loaders, excavators, and skid-steer loaders) of different sizes. The combination of electric or hydraulic hybrid systems for energy recovery (for a single actuator) with VC actuation for the rest of the actuators has also been recently deployed by original equipment manufacturers (OEMs) on some excavator models. The combination of DC actuation together with a series hydraulic hybrid actuator for the swing drive has been previously proposed and implemented as part of this work, on a mini-excavator. This combination of highly efficient DC actuation with hydraulic hybrid configuration allows drastic engine downsizing and efficiency improvements of more than 50% compared to modern-day VC-actuated systems. With a conservative, suboptimal supervisory control, it was previously demonstrated that over 50% energy savings with a 50% downsized engine over the standard load-sensing (LS) architecture for a 5-t excavator application. The problem of achieving maximum system efficiency through near-optimal supervisory control (or system power management) is a theoretically challenging problem, and has been tackled for the first time in this work for DC hydraulic hybrid machines, through a two-part publication. In Part I, the theoretical aspects of this problem are outlined, supported by simulations of the theoretically optimal supervisory control as well as an implementable, near-optimal rule-based supervisory control strategy that included a detailed system model of the DC hybrid hydraulic excavator. In Part II, the world's first prototype DC hydraulic hybrid excavator is detailed, together with machine implementation of the novel supervisory control strategy proposed in Part I. The main contributions of Part I are summarized below. Dynamic programming (DP) was employed to solve the optimal supervisory problem, and benchmark implementable strategies. Importantly, the patterns in optimal state trajectories and control histories obtained from DP were analyzed and identified for different working cycles, and a common pattern was found for engine speed and DC unit displacements across different working cycles. A rule-based strategy was employed to achieve near-optimal system efficiency, with the design of the strategy guided by optimal patterns. It was found that the strategy replicates optimal system behavior with the same rule for controlling engine speed for different cycles, but different rules for the primaiy unit (of the series-hybrid swing drive) for different cycles. Thus, in terms of practical implementation of a rulebased approach, the operator is to be provided with a family of controllers from which one can be chosen so as to have near-optimal system behavior under all kinds of cyclical operation. [ABSTRACT FROM AUTHOR]

Many railway construction and maintenance machines have large masses and perform repetitive working cycles with frequent stops that require precise positioning. For these reasons, a hydraulic propulsion system is a convenient choice. Common existing solutions make use of valve-controlled hydraulic circuits where inefficient fluid throttling takes place. Most of the time, dissipative braking is realized resulting in a remarkable quantity of available energy being wasted (up to 36 kJ of kinetic energy is available in the reference application). Additionally, the machine's automated positioning is a critical aspect. On some commercialized solutions, an overshoot of the desired final position is commonplace requiring a reverse motion in order to match the location of the desired working point. This is a negative characteristic as it introduces unnecessary fuel consumption and slows down productivity. Moreover, consideration of the limited adhesion in the wheel!rail interface is of critical importance. The propulsion system needs to be capable of differentiating the tractive or the braking torques between the driven axles. To this end, the paper proposes and analyzes a displacement-controlled (DC) propulsion system for a railway maintenance machine. The target is the removal of the fluid throttling mentioned above by defining an efficient hydraulic system. The ability to recover energy via regenerative breaking becomes a key process in improving the global machine efficiency. Simultaneously, an implementable control strategy is required for the proposed architecture to prevent overshoot of the desired position while stopping. To that end, this paper presents the mathematical model of the proposed layout used to simulate the system's behavior in order to confirm proper functioning. This work concludes with a discussion and definition of future improvements. [ABSTRACT FROM AUTHOR]

Displacement-controlled (DC) actuation is a revolutionary fluid power technology which has been utilized on a broad range of applications demonstrating substantial fuel savings and significant peiformance improvements over traditional valve-controlled (VC) systems. In this paper, a nonlinear discontinuous projection-based adaptive controller is synthesized to achieve precision motion control of DC actuators. The controller is formulated to compensate for uncertain parameters through online parameter adaptation. Additionally, its structure allows for the inclusion of unmodeled nonlinearities such as friction and external loads and disturbances. Transient performance and tracking accuracy are also guaranteed in the presence of both parametric uncertainties and uncertain nonlinearities, and asymptotic tracking is achieved in the presence of parametric uncertainties. To evaluate the synthesized controller, a test bench comprising a targe hydraulically powered end-effector was utilized. The actuator, a vane-type hydraulic motor is mechanically connected to a large robotic arm with a wide range of motion. Measurement results demonstrate that the synthesized controller achieves the aforementioned advantages while attaining a high degree of motion accuracy. [ABSTRACT FROM AUTHOR]

Increased environmental awareness and skyrocketing fuel prices have pressed researchers and engineers to find energy efficient alternatives to traditional approaches. A novel steer-by-wire technology, which is based on pump displacement control actuation, has been proposed by the authors and was shown to improve the fuel efficiency of a wheel loader steering system by 43.5%. Building on this realization, the work in this paper deals with designing an adaptive velocity controller, which takes the forni of an indirect self-tuning regulator that has the facility to cope with parametric uncertainties and uncertain nonlinearities associated with hydraulically actuated systems. The indirect self-tuning regulator algorithm is selected given that the uncertain plant parameters are estimated in the process, which is a useful byproduct that gives insight into system properties that will be considered in future investigation. Furthermore, a discrete adaptive control law with low computational cost is required for the application on hand. The designed self-tuning regulator and the estimation algorithm were validated in numerical simulations as well as experimentally on a designated prototype test vehicle, demonstrating the effectiveness of the proposed adaptive scheme in the face of uncertainties. The controller was able to adapt to varying load mass and inertia, which correlate to varying operating conditions that influence the system dynamics. Hence, besides offering improved fuel efficiency, the new steering technology also results in smarter machines. [ABSTRACT FROM AUTHOR]