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where 𝑘_𝑓 is the positive control gain. The air mass flow rate can later be related to the fan speed due to a proportional relationship.

5.5 Numerical Results and Discussion of System Performance

The proposed thermal management design was simulated for various ambient and road conditions using the Urban Assault driving cycle (Fig. 5.7a). A six wheeled 4500kg series hybrid UAGV with 380kW peak power was investigated. The vehicle features 60kW electric motors located at each wheel and a 70kW∙h battery pack. A 100kW diesel engine generator charges the battery and powers the e-motors for extended travel range. A summary of the thermal model and controller parameters are listed in Table 5.1.

Table 5.1: Summary of thermal system and controller parameters

Symbol Value Unit Symbol Value Unit Symbol Value Unit different road grades (i.e., 0%, 15%, 30%) are shown in Fig. 5.7.

The engine does not operate for 0% road grade leading to an all-electric mode. At higher road grades, or low battery state of charge, the diesel engine generator provides an average 30kW power to charge the battery (maintain a minimum SOC level) and 70 kW to drive the e-motors. The heat loads are 5,090kJ, 89,700kJ, and 13,700kJ for the above road grades, respectively.

The cooling system performance is investigated for nine scenarios based on three road grades (0%, 15%, 30%), two ambient conditions (25°C, 40°C), and different actuator configuration. Tests 3, 6, and 9 (refer to Table 5.2) only use liquid cooling for the e-motors to enable comparisons with the potential heat pipe’s energy savings and temperature tracking capabilities. The e-motor, battery pack, and engine reference temperatures are set at 70°C, 35°C, and 90°C. The total simulation time was 1,800 seconds (30 minutes).

Test 2 corresponds to a lower heat generation case based on 0% road grade and higher ambient air temperature. Using e-motor heat pipe cooling and battery AC air

Figure 5.7: UAGV operating on an Urban Assault driving cycle - (a) Vehicle speed profile, (b-d) Heat generation profiles for E-motor, battery, and engine at 0%, 15%, and

30% grades.

cooling, the system maintained satisfactory component temperatures (Fig. 5.8). The electric motor’s stator temperature stayed below 70°C using only passive heat pipe cooling. The battery core temperature was maintained about the reference temperature of 35°C. However, AC cooling was required due to the high ambient temperature which exceeded the battery reference temperature. For comparison purposes, Test 3 was conducted in which only liquid cooling was available for the e-motors and AC cooling on the battery pack. An extra 23kJ energy was consumed in these configurations without heat pipes given the difference in ambient surroundings (e.g., 70°C vs 40°C).

A higher heat generation condition was considered in Test 7 with a 30% road grade and a 25°C ambient temperature. The stator temperature (refer to Fig. 5.9a) displays a rising profile for 0 < 𝑡 < 343𝑠 to 𝑇_𝑒𝑟 = 70°C and beyond which heat pipe cooling is insufficient. Afterwards, hybrid cooling with liquid started and maintained the temperature with a 2.1°C mean error. The battery cooling system, with switching ambient and AC air, regulated the battery core temperature around 𝑇_𝑏𝑟 = 35°C with a mean error

Figure 5.8: Test 2 – Electric motor and battery temperature plots for Urban Assault driving cycle under 0% road grade with 40°C ambient temperature.

of 0.3°C per Fig. 5.9b. Finally, the engine coolant temperature stayed about 𝑇_𝑒𝑟 = 90°C by liquid cooling system as shown in Fig. 5.9c. Greater energy consumption, 5,900 kJ, occurred due to the higher heat generation.

(a)

(b)

(c)

Figure 5.9: Test 7 – Temperature plots for Urban Assault driving cycle subjected to a 30% road grade and 25°C ambient temperature for (a) Electric motor, (b) Battery pack,

and (c) Diesel engine

All test results are summarized in Table 5.2. The energy savings, up to approximately 2,960kJ, were observed using heat pipe by reducing the workload of the liquid cooling pathway. The proposed controllers collectively offer motor, battery, and engine at the reference setpoints with nominal tracking errors.

Table 5.2: Numerical study results for thermal management system undergoing Urban Assault driving cycle

Cooling Method Cooling System Energy Consumption (kJ)

(Hp – Heat pipe cooling, Liq – Liquid cooling, Amb – Ambient air ventilation, AC – AC cooling)

5.6 Summary

A holistic powertrain thermal management system for a hybrid UAGV was designed, modeled, and numerically simulated. The e-motor uses a liquid-heat pipe hybrid cooling system through an innovative thermal cradle. The battery cooling system combines ambient cooling with the vehicle’s air conditioner while the engine uses regular liquid cooling. A series of thermal models for the heat generating components, including the electric motor, battery pack, and internal combustion engine, have been mathematically developed. An urban assault driving cycle with multiple road grades and ambient conditions was considered in the simulation. Numerical results show that the heat pipes provide an additional pathway for heat rejection in e-motor cooling which saves up to approximately 2,960kJ of energy over the 1,800s simulation. The battery cooling system

can select between ambient and AC refrigerated air to maintain the battery core temperature. The benefits of using heat pipes, for e-motor and battery, and three nonlinear controllers allow minimal energy use and satisfactory temperature tracking.

CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS

The automobile cooling system configuration has remained fixed for many decades which tends to be insufficient for more complex HEV applications, having additional components (i.e. electric motors, battery pack), that have better use of fossil fuel resources.

This dissertation presents the comprehensive work conducted on HEV powertrain thermal management systems while combine heat pipes with advanced control algorithms to improve the temperature tracking performance and reduce the cooling system power consumption. The study topics included the design of innovative hybrid cooling architectures, mathematical modeling, system integration, and holistic control of multiple computer-controlled cooling actuators. The thermal management system investigation included modeling and control of electric motors, a battery pack, and an IC engine. The system performance has been evaluated using a hybrid vehicle simulation under various driving cycles, road grades, and ambient conditions.

In Chapter 2, a thermal management system for electric motors using heat pipes has been designed and simulated. A circular-shaped integrated thermal structure, or cradle, has been designed to transfer heat between the motor housing and the inserted heat pipe array.

The heat pipes function as a thermal bus to reject the generated heat to the ambient surroundings efficiently. A reduced order state-space electric motor thermal model has been developed to investigate the motor inner temperature field based on pre-calculated FEA results. Heat pipes were modeled using COMSOL^® integrating heat transfer and vapor flow. The cooling system performance was investigated based on a hybrid vehicle

simulation using two representative driving cycles (e.g., Urban Assault and Convoy Escort). Numerical results show that the electric motor stator’s hot temperature elements can be maintained below 70°C with heat pipe free convection without extra energy loss when compared with traditional liquid cooling system having a pump and fan for selected operating scenarios. With heat pipe forced convection, the motor’s temperature is maintained below 55°C with a lower energy consumption when compared with liquid cooling.

Chapter 3 extends the work done in Chapter 2 by introducing a motor hybrid cooling system featuring heat pipes integrated with liquid cooling in a compact thermal cradle. This innovative design allows heat removal via two parallel thermal pathways. The electric motor’s internal hot spots were predicted using a reduced order thermal model. A nonlinear controller was designed to maintain the motor temperature within the prescribed limits while minimizing energy consumption by regulating multiple actuators (e.g., centrifugal fan, radiator pump, and fan) operations. The cooling system performance was estimated using an Urban Assault driving cycle at various road grades (e.g., 0%, 20%) and ambient temperatures (e.g., 20°C, 40°C). Numerical results showed that the motor temperature was maintained about 70°C with heat pipe cooling, at 0% road grade with small energy consumption. At 20% road grade hybrid cooling was required, liquid cooling added with heat pipes, to maintain the motor’s temperature. The hybrid cooling system saved approximately 370kJ of energy compared to a conventional liquid cooling system due to the addition of heat pipes.

In Chapter 4, a smart battery thermal management system for hybrid electric vehicles has been developed which uses heat pipes in the thermal bus to efficiently remove heat. Two cooling loops (e.g., traditional ambient air ventilation, a standard AC system) were designed for reduced system energy consumption. A mode switch strategy was derived to select the optimal cooling loop. Nonlinear model predictive controllers were developed to maintain the battery core temperature within a designated range using either AC compressor or fan speed as the control input. The system performance was studied based on a hybrid electric vehicle simulation which runs at various driving cycles and ambient temperatures. The numerical results showed that the proposed cooling system can maintain the battery core temperature about the reference value, with a 2.1°C maximum temperature tracking error. The simulation results demonstrated that the cooling system has the ability to adapt to different ambient conditions through the selection of the suitable cooling loop with accompanying controller.

In Chapter 5, the thermal management system design research from the previous efforts was extended to develop a holistic thermal management system for a hybrid unmanned autonomous vehicle. A series of mathematical models for the vehicle powertrain components have been developed, which include electric the motors, battery pack, and small diesel engine generator. Heat pipes were used for cooling the electronics (e.g., electric motors, battery pack) since they have been proven to be an efficient and energy saving thermal regulating device. For the diesel engine, traditional liquid cooling was applied. Advanced control algorithms (e.g., optimal, nonlinear) were designed to maintain these thermal loads’ temperatures by regulating multiple actuators (e.g., pump, radiator

fan, smart valve, blower, and AC compressor) to minimize temperature spikes and reduce energy consumption. The cooling system performance was estimated based on a vehicle level simulation with various road grades and ambient conditions. Computer results showed that using heat pipes, for e-motor and battery, and the proposed controllers allow minimal energy use and satisfactory temperature tracking.

In this dissertation, the accomplished research work has established a fundamental basis for improved thermal management system performance by introducing heat pipes and applying advanced control theories. Heat pipes have been shown to be an efficient and energy saving thermal regulating devices for electronics (e.g., motors, battery). The research results demonstrated significant advantages in both the temperature tracking and energy saving by introducing the advanced model-based control theory and integrating heat pipes into traditional liquid cooling system. In the future, cooling system will likely feature multiple components as heat transfer pathways to conserve energy and operate in an optimal mode. The following work is recommended for future study.

A. Experimental tests would be valuable for the e-motor hybrid cooling concept validation and improvement. In the previous study, the e-motor thermal model has been experimentally validated using speed and torque profiles without considering the cooling system. At this point, the cooling system parameter selection is based on the material specification, system size, and data reported in previous papers.

B. Providing the mathematical proof for the optimal and model predictive controllers stabilities would be meaningful. In the current study, the system

stability can be observed from the results corresponding to the real-life driving cycles within the prescribed simulation time range.

C. Apart from exploring the advantages of heat pipes and advanced controllers to improve the cooling system performance, innovation of cooling system architecture using vehicle components as multi-functional devices may serve great benefits (e.g., the autonomous vehicle chassis may be used as a supplementary heat sink).

APPENDICES

APPENDIX A. SUPPLEMENTARY MATERIAL FOR CHAPTER 4 ADDITIONAL TEMPERATURE RESULTS

In this Appendix, additional temperature results for Tests 2, 3, and 4 in Chapter 4 will be presented as shown in Figure A.1.

(a)

(b)

(c)

Figure A.1: Simulated Temperature Results of the Battery Core, 𝑇_𝑐, Battery Surface, 𝑇_𝑠, and Cooling Air, 𝑇_𝑎 for: (a) Test 2-Urban Assault driving cycle, 𝑇_∞= 25°C, (b) Test 3- Urban Assault driving cycle, 𝑇_∞ = 40°C, and (c) Test 4-Convoy Escort driving

cycle, 𝑇_∞ = 10°C

APPENDIX B. SUPPLEMENTARY MATERIAL FOR CHAPTER 5 ADDITIONAL TEMPERATURE RESULTS

In this Appendix, the temperature results for Tests 1, 3, 4, 5, 6, 8, and 9 in Chapter 5 will be presented (Figure B.1 – B.7). Note that in Tests 3, 6, and 9, the electric motors were cooled only by liquid for comparison purposes.

(a)

(b) Figure B.1: Test 1 – Temperature plots for Urban Assault driving cycle subjected to a

0% road grade and 25°C ambient temperature for (a) Electric motor, and (b) Battery pack

(a)

(b) Figure B.2: Test 3 – Temperature plots for Urban Assault driving cycle subjected to a

0% road grade and 40°C ambient temperature for (a) Electric motor, and (b) Battery pack

(a)

(b)

(c)

Figure B.3: Test 4 – Temperature plots for Urban Assault driving cycle subjected to a 15% road grade and 25°C ambient temperature for (a) Electric motor, (b) Battery pack,

and (c) Diesel engine

(a)

(b)

(c)

Figure B.4: Test 5 – Temperature plots for Urban Assault driving cycle subjected to a 15% road grade and 40°C ambient temperature for (a) Electric motor, (b) Battery pack,

and (c) Diesel engine

(a)

(b)

(c)

Figure B.5: Test 6 – Temperature plots for Urban Assault driving cycle subjected to a 15% road grade and 40°C ambient temperature for (a) Electric motor, (b) Battery pack,

and (c) Diesel engine

(a)

(b)

(c)

Figure B.6: Test 8 – Temperature plots for Urban Assault driving cycle subjected to a 30% road grade and 40°C ambient temperature for (a) Electric motor, (b) Battery pack,

and (c) Diesel engine

(a)

(b)

(c)

Figure B.7: Test 9 – Temperature plots for Urban Assault driving cycle subjected to a 30% road grade and 40°C ambient temperature for (a) Electric motor, (b) Battery pack,

and (c) Diesel engine

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