Nonlinear model predictive control for thermal management in plug-in hybrid electric vehicles

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.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 good 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 (LV) 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 arises as 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 (HV) battery and the power electronics (PE) 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 multi- domain 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 2C. 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 to the finite-state machine-based strategy performed in the real vehicle. The results show that NMPC keeps the battery at healthier temperatures and in addition reduces the cooling electrical consumption by more than 5%. In terms of the objective function, an accumulated and weighted sum of the two goals, this improvement amounts 30%. Finally, the online SIL presented in this paper, suggests that the used optimizer is fast enough for a future implementation in the vehicle.Accepted versio

Design, Modeling and Control of a Thermal Management System for Hybrid Electric Vehicles

Hybrid electric vehicle (HEV) technology has evolved in the last two decades to become economically feasible for mass produced automobiles. With the integration of a lithium battery pack and electric motors, HEVs offer a significantly higher fuel efficiency than traditional vehicles that are driven solely by an internal combustion engine. However, the additional HEV components also introduce new challenges for the powertrain thermal management system design. In addition to the common internal combustion engine, the battery pack, the generator(s), as well as the electric motor(s) are now widely applied in the HEVs and have become new heat sources and they also require proper thermal management. Conventional cooling systems have been typically equipped with a belt driven water pump and radiator fan, as well as other mechanical actuators such as the thermostat valve. The operation of these components is generally determined by the engine speed. This open-loop cooling strategy has a low efficiency and suffers the risk of over-cooling the coolant and components within the system. In advanced thermal management systems, the mechanical elements are upgraded by computer controlled actuators including a servo-motor driven pump, variable speed fans, a smart thermostat, and an electric motor driven compressor. These electrified actuators offer the opportunity to improve temperature tracking and reduce parasitic losses. This dissertation investigates a HEV powertrain thermal management system featuring computer controlled cooling system actuators. A suite of mathematical models have been created to describe the thermal behaviour of the HEV powertrain components. Model based controllers were developed for the vehicle\u27s cooling systems including the battery pack, electric motors, and internal combustion engine. Optimal control theory has been applied to determine the ideal battery cooling air temperature and the desired heat removal rate on e-motor cooling surface. A model predictive controller(MPC) was developed to regulate the refrigerant compressor and track the battery cooling air temperature. A series of Lyapunov-based nonlinear controllers have been implemented to regulate the coolant pumps and radiator fans in the cooling systems for the engine and e-motors. Representative numerical results are presented and discussed. Overall, the proposed control strategies have demonstrated the effectiveness in improving both the temperature tracking performance and the cooling system power consumption reduction. The peak temperature error in the selected A123 battery core can be tracked within 0.25 C of the target; a 50% reduction of the vapor compression system energy consumption can be obtained by properly designing the cooling air flow structure. Similarly, the cooling system of HEV electric motors shows that the machine internal peak temperature can be tracked to the target value with a maximum error of 3.9 C and an average error of 0.13 C. A 70% to 81% cooling system energy consumption reduction can be achieved under different driving cycle comparing to classical controller applied to maintain a similar level of hotspot temperature stabilization. The proposed optimal nonlinear controller tracks the engine coolant temperature with an average error of 0.35 C and at least 13% reduction in engine cooling power. Further, a close analysis on the cooling system energy consumption reduction has been conducted with a heat exchanger simulation tool established for cooling system design optimization. This research has developed the basis for the holistic control of HEV powertrain thermal management systems by including a suite of model based nonlinear controllers to simultaneously regulate the cooling actuators for the battery pack, e-motors, and conventional internal combustion engine. Numerical studies has been conducted with a high fidelity HEV model under real driving cycles to demonstrate the advantages of introducing advanced control theory into multi-mode vehicle drive systems

Nonlinear Analysis and Control of Interleaved Boost Converter Using Real-Time Cycle to Cycle Variable Slope Compensation

Switched-mode power converters are inherently nonlinear and piecewise smooth systems that may exhibit a series of undesirable operations that can greatly reduce the converter's efficiency and lifetime. This paper presents a nonlinear analysis technique to investigate the influence of system parameters on the stability of interleaved boost converters. In this approach, Monodromy matrix that contains all the comprehensive information of converter parameters and control loop can be employed to fully reveal and understand the inherent nonlinear dynamics of interleaved boost converters, including the interaction effect of switching operation. Thereby not only the boundary conditions but also the relationship between stability margin and the parameters given can be intuitively studied by the eigenvalues of this matrix. Furthermore, by employing the knowledge gained from this analysis, a real-Time cycle to cycle variable slope compensation method is proposed to guarantee a satisfactory performance of the converter with an extended range of stable operation. Outcomes show that systems can regain stability by applying the proposed method within a few time periods of switching cycles. The numerical and analytical results validate the theoretical analysis, and experimental results verify the effectiveness of the proposed approach

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

Multidisciplinary design of a micro-USV for re-entry operations

Unmanned Space Vehicles (USV) are seen as a test-bed for enabling technologies and as a carrier to deliver and return experiments to and from low-Earth orbit. USV's are a potentially interesting solution also for the exploration of other planets or as long-range recognisance vehicles. As test bed, USV's are seen as a stepping stone for the development of future generation re-usable launchers but also as way to test key technologies for re-entry operations. Examples of recent developments are the PRORA-USV, designed by the Italian Aerospace Research Center (CIRA) in collaboration with Gavazzi Space, or the Boeing X-37B Orbital Test Vehicle (OTV), that is foreseen as an alternative to the space shuttle to deliver experiments into Earth orbit. Among the technologies to be demonstrated with the X-37 are improved thermal protection systems, avionics, the autonomous guidance system, and an advanced airfram

Nonlinear Control Strategies for Advanced Vehicle Thermal Management Systems

Advanced thermal management systems for internal combustion engines can improve coolant temperature regulation and servo-motor power consumption to positively impact the tailpipe emissions, fuel economy, and parasitic losses by better regulating the combustion process with multiple computer controlled components. The traditional thermostat valve, coolant pump, and clutch-driven radiator fan are upgraded with servo-motor actuators. When the system components function harmoniously, desired thermal conditions can be accomplished in a power efficient manner. Although the vehicle\u27s mechanical loads can be driven by electric servo-motors, the power demands often require large actuator sizes and electrical currents. Integrating hydraulically-driven actuators in the cooling circuit offers higher torques in a smaller package space. Hydraulics are widely applied in transportation and manufacturing systems due to their high power density, design flexibility for power transmission, and ease of computer control. In this dissertation, several comprehensive nonlinear control architectures are proposed for transient temperature tracking in automotive cooling circuits. First, a single loop experimental cooling system has been fabricated and assembled which features a variable position smart valve, variable speed electric coolant pump, variable speed electric radiator fan, engine block, radiator, steam-based heat exchanger, and various sensors. Second, a multiple loop experimental cooling system has been assembled which features a variable position smart thermostat valve, two variable speed electric pumps, variable speed electric radiator fan, engine block, transmission, radiator, steam-based heat exchanger, and sensors. Third, a single loop experimental hydraulic-based thermal system has been assembled which features a variable speed hydraulic coolant pump and radiator fan, radiator, and immersion heaters. In the first and second configured systems, the steam-based heat exchanger emulates the engine\u27s combustion process and transmission heat. For the third test platform, immersion heating coils emulate the combustion heat. For the first configured system, representative numerical and experimental results are discussed to demonstrate the thermal management system operation in precisely tracking desired temperature profiles and minimizing electrical power consumption. The experimental results show that less than 0.2°K temperature tracking error can be achieved with a 14% improvement in the system component power consumption. In the second configured system, representative experimental results are discussed to investigate the functionality of the multi-loop thermal management system under normal and elevated ambient temperatures. The presented results clearly show that the proposed robust controller-based thermal management system can accurately track prescribed engine and transmission temperature profiles within 0.13°K and 0.65°K, respectively, and minimize electrical power consumption by 92% when compared to the traditional factory control method. Finally, representative numerical and experimental results are discussed to demonstrate the performance of the hydraulic actuators-based advance thermal management system in tracking prescribed temperature profiles (e.g., 42% improvement in the temperature tracking error) and minimizing satisfactorily hydraulic power consumption when compared to other common control method

Innovative Thermal Management Systems for Autonomous Vehicles — Design, Model, and Test

Emphasis on reducing fossil fuel consumption and greenhouse gas emissions, besides the demand for autonomy in vehicles, made governments and automotive industries move towards electrification. The integration of an electric motor with battery packs and on-board electronics has created new thermal challenges due to the heat loads\u27 operating conditions, design configurations, and heat generation rates. This paradigm shift necessitates an innovative thermal management system that can accommodate low, moderate, and high heat dissipations with minimal electrical or mechanical power requirements. This dissertation proposes an advanced hybrid cooling system featuring passive and active cooling solutions in a thermal bus configuration. The main purpose is to maintain the heat loads’ operating temperatures with zero to minimum power requirements and improved packaging, durability, and reliability. In many operating instances, a passive approach may be adequate to remove heat from the thermal source (e.g., electric motor) while a heavy load would demand both the passive and active cooling systems operate together for reduced electric power consumption. Further, in the event of a failure (e.g., coolant hose leak, radiator tube leak) in the conventional system, the passive system offers a redundant operating mode for continued operation at reduced loads. Besides, the minimization of required convective heat transfer (e.g., ram air effect) about the components for supplemental cooling enables creative vehicle component placement options and optimizations. Throughout this research, several cooling system architectures are introduced for electric vehicle thermal management. Each design is followed by a mathematical model that evaluates the steady-state and transient thermal responses of the integrated heat load(s) and the developed cooling system. The designs and the mathematical models are then validated through a series of thermal tests for a variety of driving cycles. Then, the cooling system design configuration is optimized using the validated mathematical model for a particular application. The nonlinear optimization study demonstrates that a 50\% mass reduction could be achieved for a continuous 12kW heat-dissipating demand while the electric motor operating temperature has remained below 65 centigrade degrees. Next, several real-time controllers are designed to engage the active cooling system for precise, stable, and predictable temperature regulation of the electric motor and reduced power consumption. A complete experimental setup compares the controllers in the laboratory’s environment. The experimental results indicate that the nonlinear model predictive control reduces the fan power consumption by 73% for a 5% increase in the pump power usage compared to classical control for a specific 60-minute driving cycle. In conclusion, the conducted experimental and numerical studies demonstrate that the proposed hybrid cooling strategy is an effective solution for the next generation of electrified civilian and combat ground vehicles. It significantly reduces the reliance on fossil fuels and increases vehicle range and safety while offering a silent mode of operation. Future work is to implement the developed hybrid cooling system on an actual electric vehicle, validate the design, and identify challenges on the road

FY 1991 scientific and technical reports, articles, papers, and presentations

Formal NASA technical reports, papers published in technical journals, and presentations by MSFC personnel in FY 1991 are presented. Papers of MSFC contractors are also included. The information in this report may be of value to the scientific and engineering community in determining what information has been published and what is available