Manuel Moreno-Eguilaz

Fault tolerant operation of a five phase converter for PMSM drives

In this paper a five phase fault tolerant converter is proposed for permanent magnet (PM) drives. The proposed configuration is an extension of conventional three phase double switch redundant topologies. In contrast to three phase systems, the proposed configuration has more flexibility and reliability regarding simultaneous faults in more than one phase. Different faulty cases are explained. Optimal reconfiguration strategies are derived under several faulty conditions. Design criteria are defined and a comparative loss analysis is conducted on converter behavior under various conditions. Simulation results are included to validate the theory.

Drive Cycle Identification and Energy Demand Estimation for Refuse-Collecting Vehicles

Drive cycle identification and future energy demand prediction are advantageous when developing hybrid propulsion systems. They are applicable to vehicles that are driven along the same route every day, such as busses, refuse-collecting vehicles (RCVs), or delivery vehicles. Drive cycle identification can be used to identify what power transients can be expected to prepare the power train to operate under these conditions. If the energy management algorithm of a hybrid vehicle can account for future energy demand, then it can be arranged in such a way that the non-fossil-fuel energy sources are fully depleted at the end of the drive cycle. Given that RCVs always drive in similar drive cycles, a drive cycle has been modeled and its main characteristics parameterized. The model is separated into different drive cycles that are related to different power consumption modes. In this paper, a new method to identify drive cycles and the energy left to finish a route is proposed. The drive cycle identification is based on artificial intelligence algorithms, which have been trained and tested with real data with an average efficiency in drive cycle identification of over 90%. The energy necessary to finish the route is based on vehicle energy models and statistical analysis. This method can be used in the daily management of fleet vehicles to replace fossil fuel by electric energy, as is demonstrated in the proposed examples.

A novel AC-AC converter based SiC for domestic induction cooking applications

This paper presents the analysis and design of a new high frequency ac-ac converter applied to domestic induction heating. The proposed topology uses only four switches to control power. Converter operation is same as a conventional class D inverter. Working above the resonant frequency, a sinusoidal input current and a unit power factor are obtained. To bring higher efficiency and power density, application of emerging SiC technology in proposed converter has been evaluated. The analytical and simulation results have been verified by means of a 380-W induction heating prototype.

Nonlinear Model Predictive Control for Thermal Management in Plug-in Hybrid Electric Vehicles

A nonlinear model predictive control (NMPC) for the thermal management (TM) of plug-in hybrid electric vehicles (PHEVs) is presented. TM in PHEVs is crucial to ensure high components’ performance and durability in all possible climate scenarios. A drawback of accurate TM solutions is the higher electrical consumption due to the increasing number of low-voltage actuators used in the cooling circuits. Hence, more complex control strategies are needed for minimizing components’ thermal stress and, at the same time, electrical consumption. In this context, NMPC proves to be a powerful method for achieving multiple objectives in multiple input multiple output systems. This paper proposes an NMPC for the TM of the high-voltage battery and the power electronics cooling circuit in a PHEV. It distinguishes itself from the previously NMPC reported methods in the automotive sector by the complexity of its controlled plant, which is highly nonlinear and controlled by numerous variables. The implemented model of the plant, which is based on experimental data and multidomain physical equations, has been validated using six different driving cycles logged in a real vehicle, obtaining a maximum error, in comparison with the real temperatures of 2 

Experimentally Compared Fuel Consumption Modelling of Refuse Collecting Vehicles for Energy Optimization Purposes

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Open circuit fault detection based on emerging FCS-MPC in power electronics systems

C. For one of the six cycles, an NMPC software-in-the loop (SIL) is presented, where the models inside the controller and for the controlled plant are the same. This simulation is compared with the finite-state machine-based strategy performed in the real vehicle. The results show that NMPC keeps the battery at healthier temperatures and reduces the cooling electrical consumption by more than 5%. In terms of the objective function, which is an accumulated and weighted sum of the two goals, this improvement amounts to 30%. Finally, the online SIL presented in this paper suggests that the used optimizer is fast enough for a future implementation in the vehicle.

A simple and robust method for open switch fault detection in power converters

This paper presents a novel methodology to develop and validate fuel consumption models of Refuse Collecting Vehicles (RCVs). The model development is based on the improvement of the classic approach. The validation methodology is based on recording vehicle drive cycles by the use of a low cost data acquisition system and post processing them by the use of GPS and map data. The corrected data are used to feed the mathematical energy models and the fuel consumption is estimated. In order to validate the proposed system, the fuel consumption estimated from these models is compared with real filling station refueling records. This comparison shows that these models are accurate to within 5%.

Improved open switch fault detection based on normalized current analysis in multiphase fault tolerant converters

In this paper, a novel fault detection method based on cost fault evaluation is proposed. The cost function is same as one used in finite control set model predictive control of power converters. Two simple methods are presented to locate the faulty IGBT. Considered methodology is studied for fault detection and fault tolerant operation in a five phase PMSM drive. Theory has been developed and validated by simulation results of a five phase two level converter in Matlab/Simulink.

Clamping diode caused distortion in multilevel NPC Full-Bridge audio power amplifiers

In this paper, a new fault detection method based on signal normalization using a simple trigonometric function is presented and applied to a five phase converter for fault tolerant application under nonsinusoidal unbalanced current waveforms. Generality, simplicity, ability to localize faulty switch, multiple switch fault detection and robustness are achieved using this approach. Once theory is explained, simulation results with Matlab/Simulink and experimental waveforms are described to show the effectiveness of the proposed detection method. Experimenal results corroborate these simulation results.

Thermal Management in Plug-In Hybrid Electric Vehicles: A Real-Time Nonlinear Model Predictive Control Implementation

A new open switch fault detection method based on normalized current analysis is proposed for application in multiphase fault tolerant PMSM drives. Performance characteristics of proposed method are single diagnostic variable, ability to detect open phase fault without using auxiliary variable, ability to detect multiple switch fault, simple diagnostic variable, generality, and robustness in case of high unbalanced current waveforms. Theory of diagnostic method with special multiphase drive application is developed; simulation results using Matlab/Simulink and experimental waveforms are shown to validate effectiveness of the presented fault detection method.