Abstract
This paper presents the modeling and control of a waste heat recovery systemfor a Euro-VI heavy-duty truck engine. The considered waste heat recovery system consists of two parallel evaporators with expander and pumps mechanically coupled to the engine crankshaft. Compared to previous work, the waste heat recovery system modeling is improved by including evaporator models that combine the finite difference modeling approach with a moving boundary one. Over a specific cycle, the steady-state and dynamic temperature prediction accuracy improved on average by 2% and 7%. From a control design perspective, the objective is to maximize the waste heat recovery system output power.However, for safe system operation, the vapor state needs to be maintained before the expander under highly dynamic engine disturbances. To achieve this, a switching model predictive control strategy is developed. The proposed control strategy performance is demonstrated using the high-fidelity waste heat recovery system model subject to measured disturbances from an Euro-VI heavy-duty diesel engine. Simulations are performed usinga cold-start World Harmonized Transient cycle that covers typical urban, rural and highway driving conditions. The model predictive control strategy provides 15% more time in vaporand recovered thermal energy than a classical proportional-integral (PI) control strategy. In the case that the model is accurately known, the proposed control strategy performance can be improved by 10% in terms of time in vapor and recovered thermal energy. This is demonstrated with an offline nonlinear model predictive control strategy.
Highlights
Nowadays, the primary power source for transportation is provided by internal combustion engines.Despite efforts to improve fuel economy in modern engines, approximately 60%–70% of the fuel power is still lost through the coolant and exhaust [1]
A switching model predictive control strategy is presented that considers the effect of highly dynamic engine disturbances caused by real on-road driving conditions
The measured signals used as input for the waste heat recovery (WHR) system model are: the expander speed, bypass valves duty cycle, exhaust gas mass flow rate and temperature for both the exhaust gas recirculation (EGR) and EXH evaporator
Summary
The primary power source for transportation is provided by internal combustion engines. The control strategies dedicated to automotive applications are mostly based on a proportional-integral-derivative (PID) control type of approach [7,8,9,10,11,12]. This approach is most well established for single-input single-output systems. For multiple-input multiple-output systems with constraints, a model predictive control (MPC) can be developed, which, to the authors knowledge, has not been used for automotive WHR applications. A switching model predictive control strategy is presented that considers the effect of highly dynamic engine disturbances caused by real on-road driving conditions.
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