The increased interest in massive deployment of wireless sensors and network densification requires more innovation in low-latency communication across multi-hop networks. Moreover, the resource constrained nature of sensor nodes calls for more energy efficient transmission protocols, in order to increase the battery life of said devices. Therefore, it is important to investigate possible technologies that would aid in improving energy efficiency and decreasing latency in wireless sensor networks (WSN) while focusing on application specific requirements. To this end, and based on state of the art Glossy, a low-power WSN flooding protocol, this dissertation introduces two energy efficient, cooperative transmission schemes for low-power communication in WSNs, with the aim of achieving performance gains in energy efficiency, latency and power consumption. These approaches apply several cooperative transmission technologies such as physical layer network coding and transmit beamforming. Moreover, mathematical tools such as convex optimization and game theory are used in order to analytically construct the proposed schemes. Then, system level simulations are performed, where the proposed schemes are evaluated based on different criteria. First, in order to improve over all latency in the network as well as energy efficiency, MF-Glossy is proposed; a communication scheme that enables the simultaneous flooding of different packets from multiple sources to all nodes in the network. Using a communication-theoretic analysis, upper bounds on the performance of Glossy and MF-Glossy are determined. Further, simulation results show that MF-Glossy has the potential to achieve several-fold improvements in goodput and latency across a wide spectrum of network configurations at lower energy costs and comparable packet reception rates. Hardware implementation challenges are discussed as a step towards harnessing the potential of MF-Glossy in real networks, while focusing on key challenges and possible solutions. Second, under the assumption of available channel state information (CSI) at all nodes, centralized and distributed beamforming and power control algorithms are proposed and their performance is evaluated. They are compared in terms of energy efficiency to standard Glossy. Numerical simulations demonstrate that a centralized power control scheme can achieve several-fold improvements in energy efficiency over Glossy across a wide spectrum of network configurations at comparable packet reception rates. Furthermore, the more realistic scenario where CSI is not available at transmitting nodes is considered. To battle CSI unavailability, cooperation is introduced on two stages. First, cooperation between receiving and transmitting nodes is proposed for the process of CSI acquisition, where the receivers provide the transmitters with quantized (e.g. imperfect) CSI. Then, cooperation within transmitting nodes is proposed for the process of multi-cast transmit beamforming. In addition to an analytical formulation of the robust multi-cast beamforming problem with imperfect CSI, its performance is evaluated, in terms of energy efficiency, through numerical simulations. It is shown that the level of cooperation, represented by the number of limited feedback bits from receivers to transmitters, greatly impacts energy efficiency. To this end, the optimization problem of finding the optimal number of feedback bits B is formulated, as a programming problem, under QoS constraints of 5% maximum outage. Numerical simulations show that there exists an optimal number of feedback bits that maximizes energy efficiency. Finally, the effect of choosing cooperating transmitters on energy efficiency is studied, where it is shown that an optimum group of cooperating transmit nodes, also known as a transmit coalition, can be formed in order to maximize energy efficiency. The investigated techniques including optimum feedback bits and transmit coalition formation can achieve a 100% increase in energy efficiency when compared to state of the art Glossy under same operation requirements in very dense networks. In summary, the two main contributions in this dissertation provide insights on the possible performance gains that can be achieved when cooperative technologies are used in low-power wireless networks.

Independent metering poses a possibility to improve energy efficiency of throttlecontrolled hydraulic single-rod cylinder drives. This paper deals with energetic potentials gained through variable circuitry that come along with independent metering. A method to assess energetic potentials is described, based on load specific, optimal operating modes. As a means of yielding maximum energy efficiency for a wide range of applications, a smooth mode switching algorithm that minimizes losses and allows good motion tracking is proposed. The mode switching algorithm is validated in simulation and on a test stand.

The focus of the present contribution is hydraulic energy recovery by means of hydropneumatic multi-chamber accumulators. A simulation study is presented comparing two different multi-chamber accumulator concepts for energy recovery in an exemplary load case involving a forklift mast. The first concept is based on the “Double Piston Accumulator” /1/. It is compared to the so-called “Digital Accumulator” /2/. Both similarities and differences of the two concepts are discussed in the presentation.

Speed and displacement variable pumps offer a degree of freedom for process control. As a certain operation point can be supplied by different combinations of drive speed and pump displacement intelligent control strategies can address major issues like energy efficiency, process dynamics and noise level in industrial applications. This paper will provide an overview of recent research and development activities to evaluate the named potentials.

The paper shows standard circuits with load reactive and non load reactive counterbalance valves. A Matlab simulation based on a linear model for the circuit with load reactive counterbalance valves shows what parameters have a significant influence on the stability of the system. The most important parameters of the counterbalance valve that influence the stability are pilot gain and relief gain. The factors describe how pilot pressure and load pressure affect the flow across the counterbalance valve. A new counterbalance valve (patent pending) has the pilot gain and relief gain required for stability only in operating ranges that require the parameters for stability. When the load is not moving or the counterbalance valve is not required for positive (non overrunning) loads, the new valve has a higher pilot ratio, which means that the valve opens further at lower inlet pressures. The new counterbalance valves saves about 30% power compared with a standard counterbalance valve that has the same parameters for stability when it is lowering an overrunning load. The standard counterbalance can be replaced with the new load adaptive valve in the same cavity. The paper shows test results and the design of the valve.

Pneumatic linear drives are widely used in manufacturing, mainly for handling tasks. Due to rising interest in environmental matters and increasing energy costs, energy efficiency has become a major issue in industrial applications. There is a growing competition between pneumatic and electromechanical drives. Pneumatic drives are said to have a lower efficiency while the initial costs of electromechanical drives are higher. The operating costs of electromechanical as well as pneumatic drives are induced by their exergy efficiency. The efficiency of the drives depends on parameters like cycle time, load applied to the cylinder and its acceleration and velocity. Former research did only provide limited data on the influence of these parameters. The paper provides an overview on the exergy efficiency of pneumatic and electromechanical drives and its dependency on the mentioned parameters. Since electromechanical drives are often used to replace pneumatic drives both technologies are examined in typical applications for pneumatic drives, including horizontal and vertical movement and sustaining a load for different periods in vertical usage.

This paper is presenting the application of Power Regenerative Boom(PRB) system to excavator. In order to increase the fuel efficiency of the excavator, potential energy of the front structure is recuperated by the hydraulic hybrid system with electric-hydraulic control, during boom down motion. Charged energy into accumulator is reused after boom down motion, the pressurized oil goes to hydraulic motor. The hydraulic motor is mounted on the engine PTO(Power Take-Off), therefore output torque of the hydraulic motor assists the diesel engine directy, it leads to decrease fuel consumption of diesel engine. After the system design and simulation investigation, the presented system was installed into Doosan’s 38ton excavator, DX380LC-3 model, and the energy saving result was verified by a digging and dumping repetition test. The test result shows that fuel consumption was dramatically decreased by 5.0 L/hr compared to the standard DX380LC-3.

>Magister Scientiae - MSc / The fifth-generation mobile network (5G) is a new global wireless standard that enables state-of-the-art mobile networks with enhanced cellular broadband services that support a diversity of devices. Even with the current worldwide advanced state of broadband connectivity, most rural and low-income settings lack minimum Internet connectivity because there are no economic incentives from telecommunication providers to deploy wireless communication systems in these areas. Using a team of Unmanned Aerial Vehicles (UAVs) to extend or solely supply the 5G coverage is a great opportunity for these zones to benefit from the advantages promised by this new communication technology. However, the deployment and applications of innovative technology in rural locations need extensive research.

During the last decade, relay networks have attracted a lot of interest due to their numerous benefits. The relaying technique allows extending the coverage zone of wireless networks and offers a higher reliability for communication systems. The performance of relay networks can be improved further by the use of automatic repeat request (ARQ) and hybrid automatic repeat request (HARQ) techniques. ARQ and HARQ are retransmission mechanisms that ensure a good quality of service even in absence of channel state information at the transmitter. We, firstly, study the spectral and energy efficiency of ARQ in Nakagami-m block-fading channels. We maximize both spectral efficiency and energy efficiency with respect to the transmitted power. We derive exact expressions as well as compact and tight approximation for the solutions of these problems. Our analysis shows that the two problems of maximizing spectral efficiency and energy efficiency with respect to the transmitted power are completely different and give different solutions. Additionally, operating with a power that maximizes energy efficiency can lead to a significant drop in the spectral efficiency, and vice versa. Next, we consider a three node relay network comprising a source, a relay, and a destination. The source transmits the message to the destination using HARQ with incremental redundancy (IR). The relay overhears the transmitted message, amplifies it using a variable gain amplifier, and then forwards the message to the destination. This latter combines both the source and the relay message and tries to decode the information. In case of decoding failure, the destination sends a negative acknowledgement. A new replica of the message containing new parity bits is then transmitted in the subsequent HARQ round. This process continues until successful decoding occurs at the destination or a maximum number M of rounds is reached. We study the performance of HARQ-IR over the considered relay channel from an information theoretic perspective. We derive exact expressions and bounds for the information outage probability, the average number of transmissions, and the average transmission rate. Moreover, we evaluate the delay experienced by Poisson arriving packets over the considered relay network. We also provide analytical expressions for the expected waiting time, the sojourn time, and the energy efficiency. The derived exact expressions are validated by Monte Carlo simulations. Finally, we consider a relay network consisting of a source, K relays, and a destination. The source transmits a message to the destination using HARQ-IR. We study the performance of HARQ-IR over dualhop multibranch amplify-and-forward relay channels. We derive exact expression for outage probability of the considered network. We investigate the benefit of relaying and the effect of changing the rate and the maximum number M of rounds on the outage probability.

<p>Commercial buildings not only have significant impacts on occupants’ well-being, but also contribute to more than 19% of the total energy consumption in the United States. Along with improvements in building equipment efficiency and utilization of renewable energy, there has been significant focus on the development of advanced heating, ventilation, and air conditioning (HVAC) system controllers that incorporate predictions (e.g., occupancy patterns, weather forecasts) and current state information to execute optimization-based strategies. For example, model predictive control (MPC) provides a systematic implementation option using a system model and an optimization algorithm to adjust the control setpoints dynamically. This approach automatically satisfies component and operation constraints related to building dynamics, HVAC equipment, etc. However, the wide adaptation of advanced controls still faces several practical challenges: such approaches involve significant engineering effort and require site-specific solutions for complex problems that need to consider uncertain weather forecast and engaging the building occupants. This thesis explores smart building operation strategies to resolve such issues from the following three aspects. </p> <p>First, the thesis explores a stochastic model predictive control (SMPC) method for the optimal utilization of solar energy in buildings with integrated solar systems. This approach considers the uncertainty in solar irradiance forecast over a prediction horizon, using a new probabilistic time series autoregressive model, calibrated on the sky-cover forecast from a weather service provider. In the optimal control formulation, we model the effect of solar irradiance as non-Gaussian stochastic disturbance affecting the cost and constraints, and the nonconvex cost function is an expectation over the stochastic process. To solve this optimization problem, we introduce a new approximate dynamic programming methodology that represents the optimal cost-to-go functions using Gaussian process, and achieves good solution quality. We use an emulator to evaluate the closed-loop operation of a building-integrated system with a solar-assisted heat pump coupled with radiant floor heating. For the system and climate considered, the SMPC saves up to 44% of the electricity consumption for heating in a winter month, compared to a well-tuned rule-based controller, and it is robust, imposing less uncertainty on thermal comfort violation.</p> <p>Second, this thesis explores user-interactive thermal environment control systems that aim to increase energy efficiency and occupant satisfaction in office buildings. Towards this goal, we present a new modeling approach of occupant interactions with a temperature control and energy use interface based on utility theory that reveals causal effects in the human decision-making process. The model is a utility function that quantifies occupants’ preference over temperature setpoints incorporating their comfort and energy use considerations. We demonstrate our approach by implementing the user-interactive system in actual office spaces with an energy efficient model predictive HVAC controller. The results show that with the developed interactive system occupants achieved the same level of overall satisfaction with selected setpoints that are closer to temperatures determined by the MPC strategy to reduce energy use. Also, occupants often accept the default MPC setpoints when a significant improvement in the thermal environment conditions is not needed to satisfy their preference. Our results show that the occupants’ overrides can contribute up to 55% of the HVAC energy consumption on average with MPC. The prototype user-interactive system recovered 36% of this additional energy consumption while achieving the same overall occupant satisfaction level. Based on these findings, we propose that the utility model can become a generalized approach to evaluate the design of similar user-interactive systems for different office layouts and building operation scenarios. </p> <p>Finally, this thesis presents an approach based on meta-reinforcement learning (Meta-RL) that enables autonomous optimal building controls with minimum engineering effort. In reinforcement learning (RL), the controller acts as an agent that executes control actions in response to the real-time building system status and exogenous disturbances according to a policy. The agent has the ability to update the policy towards improving the energy efficiency and occupant satisfaction based on the previously achieved control performance. In order to ensure satisfactory performance upon deployment to a target building, the agent is trained using the Meta-RL algorithm beforehand with a model universe obtained from available building information, which is a probability measure over the possible building dynamical models. Starting from what is learned in the training process, the agent then fine-tunes the policy to adapt to the target building based on-site observations. The control performance and adaptability of the Meta-RL agent is evaluated using an emulator of a private office space over 3 summer months. For the system and climate under consideration, the Meta-RL agent can successfully maintain the indoor air temperature within the first week, and result in only 16% higher energy consumption in the 3^rd month than MPC, which serves as the theoretical upper performance bound. It also significantly outperforms the agents trained with conventional RL approach. </p>