Model Predictive Control for Engine Powertrain Thermal Management Applications

<div class="section abstract"><div class="htmlview paragraph">Electric vehicle thermal management system is essential for electric vehicles to guarantee cabin thermal comfort and battery appropriate operating temperature. As a matter of fact, in such systems, high- and low-temperature driving conditions can severely affect system performance, in terms of overall efficiency and driving range. In this context, an effective thermal management solution both for cabin thermal comfort and battery heating/cooling is investigated in this paper.</div><div class="htmlview paragraph">A key innovation is the deep integration of the HVAC and battery heating/cooling circuits. Primarily, in winter scenario, the heat generated by the powertrain during operation is used to warm the cabin, thereby mitigating the necessity for additional electric cabin heating. This way, despite the inclusion of an extra heat exchanger, a consistent amount of heat can be recovered and the use of the battery energy for electrical heating activation is significantly reduced, as already presented by the authors in a previous study. Furthermore, the HVAC sub-system is designed so as to streamline hot or fresh air to the battery for heating or cooling purposes, respectively, resulting in a comprehensive and integrated solution that enhances overall energy efficiency, with minimum penalizations in cabin comfort.</div><div class="htmlview paragraph">This evaluation employs a 1-D model of the HVAC and battery heating/cooling integrated circuit and a 0-D model to interface it with the vehicle powertrain. A second order electrical equivalent circuit model is employed for the battery, to better capture transient behavior and heat generation, with all the parameters in the model being temperature-and SoC-dependent. Different control strategies are proposed for the management of the thermal system and various driving conditions, including scenarios during summer and winter with different speed profiles, are taken into account to assess their performance.</div><div class="htmlview paragraph">It is important to note that while this integrated approach introduces a degree of complexity, the benefits in terms of energy efficiency are shown to be substantial if the system control logic is designed properly. This multi-faceted analysis contributes valuable insights to the ongoing discourse on optimizing electric powertrains for enhanced performance and efficiency under diverse operating conditions.</div><div class="htmlview paragraph">The analysis carried out allows to effectively determine the influence of the HVAC sub-system on the battery state of charge, and then in terms of driving range, i.e. for the Helsinki driving cycle, the deactivation of the cabin heating allows the increase of about the 30% the driving time. It has been also highlighted how the different control strategy can influence the average battery temperature and as a consequence its internal resistance especially during winter scenario. Due to the high thermal load required during the summer driving conditions, the control strategy seems to be less effective.</div></div>

<div class="section abstract"><div class="htmlview paragraph">Combustion simulations and single cylinder engine tests show a clear potential when coupling the Variable Compression Ratio (VCR) engine with the Variable Valve Actuation (VVA) technologies.</div><div class="htmlview paragraph">Simulations demonstrate the thermodynamic benefit from increasing the geometric Compression Ratio (CR>18:1) in combination with VVA compared to VVT strategies, thanks to the use of Atkinson / Miller Cycles. 3D combustion simulations of high compression ratio combustion chamber geometries used with Early or Late Intake Valve Closing strategies have been carried out with IFP-C3D™. They show an indicated efficiency increase up to 12 or 13% between compression ratio 10:1 and 18-20:1 at low loads (BMEP < 8 bar).</div><div class="htmlview paragraph">Single cylinder engine tests have been performed with specific combustion chambers up to CR 23:1 and have confirmed the simulation results.</div><div class="htmlview paragraph">0D GT-POWER™ simulations have been correlated to the engine tests and used to extrapolate them to a 3 cylinders 1.1L TGDI VCR-VVA engine, for both EIVC and LIVC intake valve lift strategies.</div><div class="htmlview paragraph">Finally, simulations and tests show correlated thermodynamic benefits of the association of VCR and VVA, improving fuel consumption on driving cycles between 8 and 11% compared to a 10.5:1 fixed compression ratio engine equipped with 2 VVT. Combining the VCR and VVA optimizes each potential far more than when separated (alone). Furthermore, the fuel consumption benefit is robust through driving cycles and downsizing level. </div></div>

<div class="section abstract"><div class="htmlview paragraph">This paper presents the design, implementation, and performance evaluation of a reduced complexity algorithm for a predictive control which is based on our previously published SAE paper (2021-01-0225) titled, “Model Predictive Control for Engine Thermal Management System.” That paper presented a model predictive control (MPC) design concept and demonstrated energy efficiency improvements by enabling engine pre-cooling based on GPS/Navigation data to recognize future vehicle speed limit and road grade in anticipation of high engine load demand.</div><div class="htmlview paragraph">When compared to conventional control, the predictive control demonstrated considerable energy and fuel savings due to delayed timing of both knock mitigation and activation of radiator cooling fan during high engine load demand. However, this predictive control strategy is much more complicated due to its highly coupled nonlinear behavior. Also, in reality, the previous developed MPC strategies are limited to the computational resources in engine control units (ECU). Therefore, to address these challenges, a reduced-complexity MPC controller for the powertrain thermal system is developed in this paper where, by “reduced-complexity,” it is meant that the MPC controller achieves control objectives and to be executed on a modern ECU within a computation budget.</div><div class="htmlview paragraph">To maximize fuel economy, one of the key control logics in the previously published SAE paper is to use estimated radiator outlet coolant temperature as an indicator to determine when to lower the target engine coolant temperature. Since the heat transfer coefficients (HTC) of the thermal system are time varying, the computation load is high if the inputs to the plant models are physics-based. Therefore, lookup table (LUT)-based and mean value model (MVM) modeling approaches are developed and combined in order to reduce computational burden.</div><div class="htmlview paragraph">The complexity reduction is obtained via lookup tables and mean value models, which lightens the computational load of the algorithm with a minimal loss in precision. Experimental results showed that the proposed approach is able to deliver performance similar to originally proposed approaches. At the same time, the proposed algorithm is able to cut the computational complexity of the physics-based algorithm by an 18% factor.</div></div>

<div class="htmlview paragraph">In the past decade, SCR deNOx technology with urea injection has grown to maturity. European OEMs will apply SCR deNOx to meet future heavy-duty emissions legislation starting with EURO-4 (2005/2006). Numerous research programs in Europe and the US have shown a variety of system layouts and control strategies. The main differences are formed by:</div> <div class="htmlview paragraph"> <ul class="list disc"> <li class="list-item"><div class="htmlview paragraph">the engine-out NO<sub>x</sub> calibration</div> </li> <li class="list-item"><div class="htmlview paragraph">the application of an NO to NO<sub>2</sub> catalyst</div> </li> <li class="list-item"><div class="htmlview paragraph">open-loop or closed-loop urea dosage control.</div> </li> </ul> </div> <div class="htmlview paragraph">This paper gives an overview of possible SCR system configurations that are required for different stages of future emission legislation.</div> <div class="htmlview paragraph">Engine-out NO<sub>x</sub> emission is strongly influenced by ambient conditions. Projections in this study show that a combination of cold climate and a wintergrade fuel is the most severe: it may lead to 30% lower engine-out NO<sub>x</sub> emission with respect to laboratory conditions. The varying engine-out NO<sub>x</sub> emission requires a safety margin in the case of an open-loop controlled system in order to avoid excessive NH<sub>3</sub> slip.</div> <div class="htmlview paragraph">Calculations in this paper show that Euro 4 limits can be met with open-loop controlled urea dosage; an NO to NO<sub>2</sub> catalyst is even not required. For other future emission legislation (Euro 5, US 2007 and US 2010), it becomes difficult to safely achieve the limits with open-loop control. US 2007 and 2010 legislation require an NO to NO<sub>2</sub> catalyst because of the low average load and consequently low exhaust gas temperatures. Engines that are developed to meet US 2010 legislation need special measures to increase the exhaust gas temperature and to reduce engine-out NO<sub>x</sub> below 2 g/kWh.</div> <div class="htmlview paragraph">In all cases, optimal hydrolysis and mixing conditions are of major importance. High speed photography and droplet size measurements are presented as methods for characterizing and modeling aqueous urea spray patterns. The information from these measurements is used as input parameters for simulation tools. These consist of a 2D/3D CFD program for urea mixing analysis and a 1D SCR system model for development of dosage control and optimization of catalyst dimension.</div> <div class="htmlview paragraph">Finally, simulations with the SCR system model are compared with measurements on the engine test bench.</div>

<div class="section abstract"><div class="htmlview paragraph">Hybrid electric vehicle (HEVs) represents a promising approach to reduce vehicle fuel consumption and exhaust emissions. However, due to the electric motor (EM) assistance, the engine load could be reduced and intermittent operation of engine is realizable in HEVs powertrain system. Consequently, the HEV powertrain heating-up process and engine fuel consumption will be changed accordingly.</div><div class="htmlview paragraph">Therefore, the influences of the EM power and battery capacity on the hybrid powertrain heating-up process and the engine fuel consumption will be analyzed, and 2 methods for optimizing the heating-up process by applying the auxiliary heaters (AHs) and the modification of the energy management strategy are represented.</div><div class="htmlview paragraph">The application of AHs can improve engine efficiency during heating-up; the controlling of the power flow from the AHs to the ICE cooling system is of special important. Accordingly, a thermal and energy management strategy (TEMS) is introduced in this paper to find a balance between fuel consumption and heating-up.</div><div class="htmlview paragraph">The TEMS is based on model predictive control (MPC) and dynamic programming (DP). MPC analyzes the forthcoming vehicle speed profile, calculates the power requirement and controls the AH accordingly. A cost function is then formulated based on the battery SOC and other driving conditions. DP solves the objective function and optimizes the power distribution between electric motor and engine.</div><div class="htmlview paragraph">The effects of the two methods are demonstrated by simulation in Matlab/Simulink. Simulation results are compared to demonstrate the optimized heating-up process.</div></div>

<div class="htmlview paragraph"> </div> <div class="htmlview paragraph"> </div> <div class="htmlview paragraph">This paper summarizes the numerical development of a cooling package in a vehicle. The radiator and condenser fan performance curves are predicted using Computational Fluid Dynamics (CFD) approach using a numerical AMCA (Air Motion Control Association) chamber. The same procedure is extended to generate the combined fan performance curves. System resistance curves at various vehicle speeds are determined. To determine the vehicle system resistance at various vehicle speeds, a full vehicle CFD model in a numerical wind tunnel is developed and analyzed at different fan speeds.</div> <div class="htmlview paragraph"> </div> <div class="htmlview paragraph">The changes in radiator flow for different scenarios such as change in fan geometry and the removal of condenser fan are outlined in this work.</div> <div class="htmlview paragraph"> </div> <div class="htmlview paragraph">The study is then extended to predict radiator hot flow and coolant inlet temperatures at different vehicle load conditions. An analytical method to determine hot air flow and air temperature at radiator exit is developed. This approach is extended to predict coolant inlet temperatures, using the radiator performance data. This can further be used to compute the required change in radiator airflow to meet the coolant inlet temperature targets. The feasibility of removing the condenser fan and still meet the temperature targets is also outlined.</div> <div class="htmlview paragraph"> </div>

ABSTRACTThis paper presents a nonlinear model predictive control (MPC) formulation for obstacle avoidance in high-speed, large-size autono-mous ground vehicles (AGVs) with high centre of gravity (CoG) that operate in unstructured environments, such as military vehicles. The term ‘unstructured’ in this context denotes that there are no lanes or traffic rules to follow. Existing MPC formulations for passenger vehicles in structured environments do not readily apply to this context. Thus, a new nonlinear MPC formulation is developed to navigate an AGV from its initial position to a target position at high-speed safely. First, a new cost function formulation is used that aims to find the shortest path to the target position, since no reference trajectory exists in unstructured environments. Second, a region partitioning approach is used in conjunction with a multi-phase optimal control formulation to accommodate the complicated forms the obstacle-free region can assume due to the presence of multiple obstacles in the prediction horizon in an unstructured environment. Third, the no-wheel-lift-off condition, which is the major dynamical safety concern for high-speed, high-CoG AGVs, is ensured by limiting the steering angle within a range obtained offline using a 14 degrees-of-freedom vehicle dynamics model. Thus, a safe, high-speed navigation is enabled in an unstructured environment. Simulations of an AGV approaching multiple obstacles are provided to demonstrate the effectiveness of the algorithm.

<div class="section abstract"><div class="htmlview paragraph">In the present scenario, automobile manufacturers are forced to reduce the weight of each components through design optimization. In a bid to enhance the fuel efficiency and load carrying capacity of the vehicle; however this approach may not be practical for all the parts in real life, and the engineer will end up adding further mass to the component. This is carried out to enhance the strength of the component, since considerable over load application in real world usage condition which can damage the component drastically.</div><div class="htmlview paragraph">In this paper, steering tie rod arm of a heavy commercial vehicle was taken as a case study. The Steering tie rod arm is a part which connects the wheel spindle with steering system linkage i.e. Track rod. Track rod transfers the steered force from one wheel to another wheel and steering tie rod arm transfers the force from track rod to wheel spindle to steer both the wheels in same direction.</div><div class="htmlview paragraph">During vehicle operating conditions, this steering tie rod arm experiences very high tensile and compressive loads and consecutively this part undergoes fatigue. Authors discussed on initial design proposal of steering tie rod arm, CAE (Computer Aided Engineering) Analysis, Instrumentation and Vehicle data acquisition on different operating conditions, block programming of test data, life predictions using strain life approach and physical testing. The predicted life was compared with CAE life and actual component test life to establish correlation. Optimization of design was carried out virtually using this established correlation and further substantiated by rig and vehicle level testing</div></div>

<div class="htmlview paragraph">Through the rapid evolution of microcomputer capability in the field of automotive electronic fuel injection, a system has recently been developed to integrate powertrain control, unifying engine control and automatic transmission control.</div> <div class="htmlview paragraph">Implementation of advanced control theory is one of the major issues in this field and will benefit greatly from microcomputer performance improvements.</div> <div class="htmlview paragraph">This paper commences with a discussion of the trend toward higher performance requirements in integrated powertrain control, driven by a new concept in control: variable transmission shiftpoint control based on vehicle operating conditions.</div> <div class="htmlview paragraph">The latter portion of the paper describes a new 16-bit dual CPU system for integrated powertrain control. The system achieves an improvement in processing through high-density communication. Software development is also enhanced by separating the functions of the engine-control microcomputer from those of the transmission-control microcomputer and by using mutually non-interfering software.</div>

<div class="htmlview paragraph">In recent years, the fraction of air conditioning systems installed in American automobiles has increased to approximately 85%. Concurrently, efforts to improve fuel economy have resulted in smaller engines. The point has been reached in which load from a cycling fixed-displacement compressor can significantly affect vehicle drivability and performance. To remedy this problem, variable-capacity A/C systems have been developed with mechanically controlled compressor displacements.</div> <div class="htmlview paragraph">An alternative electronic approach to cooling capacity modulation is presented in this paper. The system utilizes a variable-speed brushless dc motor to drive a fixed-displacement compressor, thus achieving continuous control of cooling output independent of the engine drive belt. Compared to variable-displacement compressors, electrically driven A/C systems provide the following additional benefits: <ul class="list disc"> <li class="list-item"><div class="htmlview paragraph">Hermetic motor/compressor assembly (no shaft seal leakage)</div></li> <li class="list-item"><div class="htmlview paragraph">Smaller, less complex compressor</div></li> <li class="list-item"><div class="htmlview paragraph">Flexible packaging (no drive belt)</div></li> <li class="list-item"><div class="htmlview paragraph">Full cooling capacity at any engine speed</div></li> <li class="list-item"><div class="htmlview paragraph">Control of conditioned air temperature without reheat</div></li> </ul></div> <div class="htmlview paragraph">This paper deals with the development of a brushless dc drive system suitable for powering an automotive air conditioner. Two 5 hp motors were designed and built with maximum operating speeds of 6000 and 7000 rpm. These motors were then tested in a typical automotive air conditioning system over a range of operating conditions in order to determine their performance envelopes. The results are discussed, and conclusions are drawn as to the type of compressor and control strategy best suited for electric automotive A/C. Issues that are critical to the further development of electrically driven A/C systems are identified. An example simulation of annualized A/C system performance is also provided to quantify some of the benefits of cooling capacity modulation.</div>

<div class="section abstract"> <div class="htmlview paragraph">The SAE J3211 procedure applies to squeal evaluation for foundation brakes using single-ended inertia dynamometers for friction couples used on vehicles with regenerative braking systems. This document applies to squeal noise occurrences for on-road passenger cars and light trucks with a gross vehicle weight rating of 4536 kg or below and with at least one rechargeable energy storage system as a source for propulsion. The procedure incorporates aspects related to (a) minimum inertia dynamometer capabilities, (b) fixture requirements and setup, and (c) test sequences with emphasis on brake temperatures, brake pressure profiles, and strategies to represent brake blending.</div> <div class="htmlview paragraph">For this document, squeal occurs when the peak noise level is at least 70 dB(A) between 1.25 and 16 kHz for tests using full suspension corners or complete axle assemblies, or between 2 and 16 kHz for brakes not using an entire suspension corner.</div> <div class="htmlview paragraph">Test facilities intending to use this document, building on their expertise in conducting SAE J2521, shall review in detail the changes to test parameters (mainly brake temperatures and brake pressures) for legacy modules.</div> <div class="htmlview paragraph">This document also applies to vehicles with electromechanical braking systems to actuate the foundation brake. The test requester and the test facility are responsible for converting the hydraulic pressure levels into their equivalent clamping forces for brakes using electromechanical actuation.</div> <div class="htmlview paragraph">Before using this document for chassis dynamometer testing, review in detail the specifics related to at least (a) instrumentation, including in-cabin microphones; (b) threshold levels for noise detection; (c) temperature control priority between the front and rear axles; (d) vehicle loading and load distribution; (e) cooling air and environmental conditioning; (f) detailed terminology and labeling of channels and sensors; and (g) the regenerative settings and the state of charge during the test.</div> <div class="htmlview paragraph">Before using this document along with other methods to recreate the regenerative brake blending (e.g., Software-in-the-Loop or Hardware-in-the-Loop), consider (a) the vehicle powertrain, blending architecture and its applicable models, (b) actual profiles intended to recreate (e.g., control strategies, state of charge, test scenarios), and (c) actual embodiment of the simulation and integration with the native controls of the brake dynamometer.</div> <div class="htmlview paragraph">This document does not include noise from other sources (e.g., parking brakes, electric machines, driveline components).</div> </div>

<div class="section abstract"><div class="htmlview paragraph">The introduction of transient test cycles and the focus on real world driving emissions has increased the importance of ensuring the NO<sub>x</sub> and soot emissions are controlled during transient manoeuvres. At the same time, there is a drive to reduce the number of calibration variables used by engine control strategies to reduce development effort and costs.</div><div class="htmlview paragraph">In this paper, a control orientated combustion model, [<span class="xref">1</span>], and model predictive control strategy, [<span class="xref">2</span>], that were developed in simulation and reported in earlier papers, are applied to a Diesel engine and demonstrated in a test vehicle.</div><div class="htmlview paragraph">The paper describes how the control approach developed in simulation was implemented in embedded hardware, using an FPGA to accelerate the emissions calculations. The development of the predictive controller includes the application of a simplified optimisation algorithm to enable a real-time calculation in the test vehicle.</div><div class="htmlview paragraph">The test vehicle was calibrated over a constant speed step manoeuvre and then demonstrated over the standard US06 drive cycle, where it was found to reduce NO<sub>x</sub> and CO<sub>2</sub> emissions.</div><div class="htmlview paragraph">The paper concludes with a discussion on the merits of an emissions based engine control strategy, where the controller seeks to control emissions directly rather than an indirect quantity such as boost pressure.</div></div>

<div class="section abstract"><div class="htmlview paragraph">While hybrid electric powertrains are the standard for passenger cars, the application to motorcycles is almost nil. The reason is the increase in weight, cost and overall dimensions, which can compromise the layout and dynamics of the motorcycle. A viable path is to replace the standard internal combustion engine with a much smaller and lighter unit, which leaves room for the installation of the electric components. The 2-Stroke (2S) cycle technology, thanks to double cycle frequency and inherent simplicity, can be the key to reduce engine dimensions, weight and cost, while keeping high power outputs.</div><div class="htmlview paragraph">The HybridTec project, discussed in this paper, aims to develop a compact and lightweight V-90° two-cylinder 2S engine, coupled to an electric motor installed downstream of the gearbox (P3 configuration). The total installed power should be about 110 kW.</div><div class="htmlview paragraph">The engine features loop-scavenging, actuated by a crankshaft-driven supercharger, while an exhaust rotary valve and electronic fuel injection minimize fuel short-circuit over a broad operating range. Moreover, the control of air and residuals trapped within the cylinder is made by a bypass valve downstream of the supercharger. A 4-Stroke-like forced lubrication system is also adopted.</div><div class="htmlview paragraph">Another advantage of this engine design is the possibility to dilute the fresh charge with exhaust gas, at any operating condition: a proper percentage of residuals helps to cut NO<sub>x</sub> emissions without the need for complex and expensive after-treatment systems.</div><div class="htmlview paragraph">A single-cylinder prototype of the engine was preliminarily built and tested, the initial design being carried out with the support of a 1D model, which was then calibrated based on a preliminary configuration of the engine.</div><div class="htmlview paragraph">According to the 1D simulation results, the engine is able to meet the performance targets and shows good potential at part-load operation, but engine injection system and control strategy need further optimization, which will be supported by future detailed 3D-CFD analysis.</div></div>

<div class="section abstract"><div class="htmlview paragraph">This study focuses on enhancing energy efficiency in electric vehicle (EV) thermal management systems through the development and optimization of control logic.</div><div class="htmlview paragraph">A full vehicle thermal management system (VTMS) was modeled using GT-Suite software, incorporating subsystems such as the high voltage battery (HVB), Electric powertrain (EPT), and an 8-zone cabin. Thermal models were validated with experimental data to ensure accurate representation of key dynamics, including coolant to cell heat transfer, cell-to-ambient heat dissipation, and internal heat generation.</div><div class="htmlview paragraph">Control strategies were devised for Active Grille Shutter (AGS) and radiator fan operations, targeting both cabin cooling and EPT thermal regulation. Energy consumption was optimized by balancing aerodynamic drag, fan power, and compressor power across various driving conditions. A novel series cooling logic was also developed to improve HVB thermal management during mild ambient conditions.</div><div class="htmlview paragraph">Simulation results demonstrate significant energy savings while maintaining desired thermal performance, showcasing a systematic approach to sustainable EV thermal management</div></div>

<div class="section abstract"><div class="htmlview paragraph">Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust, which allows fuel economy (FE) improvements in hybrid electric vehicles (HEVs) through optimal energy management strategies (EMS). Velocity predictions generated between 5 and 30 s predictions could be implemented using model predictive control (MPC), but the performance of MPC must be well understood. Also, the vulnerability of predictive optimal EMS to velocity prediction accuracy should be addressed. Before an optimal EMS can be implemented, its overall performance must be evaluated and benchmarked against relevant velocity prediction metrics. A real-world highway drive cycle (DC) in the high-fidelity, controls-oriented 2017 Toyota Prius Prime model operating in charge-sustaining mode was utilized to observe FE realization. We propose three important metrics for comparison to no velocity prediction control: (1) perfect full DC prediction using dynamic programming (DP), (2) 10 s prediction horizon MPC, (3) 10 s constant velocity prediction. The very first optimal EMS requires the whole DC prediction in advance, whereas the rest of the two strategies only require limited horizon velocity prediction. These different velocity predictions are input into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. Our results show that the constant velocity prediction algorithm outperformed the baseline control strategy, but underperformed the MPC strategy. We also show that using a 10 s prediction window, MPC strategy provided FE improvement results very close to the full DC prediction case. So with the advancement in perception systems, MPC could be implementable in real vehicles. Also, constant velocity prediction results are good enough that optimization should be implemented in vehicle controllers with MPC type of framework. In future work, we seek to combine these models with velocity prediction models to demonstrate FE improvements on a physical vehicle.</div></div>