# Optimization Approaches and Techniques for Automotive Alternators: Review Study

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## Abstract

**:**

## 1. Introduction

## 2. Optimization Methods

#### 2.1. Pontryagin’s Minimum Principle (PMP)

#### 2.2. Optimal Power Distribution (OPD)

#### 2.3. Equivalent Consumption Minimization Strategy (ECMS)

#### 2.4. Model Predictive Controller (MPC) and Modified Dynamic Programming (DP)

#### 2.5. Teaching-Learning-Based Optimization (TLBO)

_{A}), for the exciter (τ

_{E}), for the generator (τ

_{G}), and the sensor (τ

_{S})) for the robust TLBO algorithm.

#### 2.6. DCR (Driving Cycle Recognition) and ELP (Electrical Load Perception) Algorithms

#### 2.7. Multi-Objective Optimization Approach

#### 2.8. Quadratic Optimization

#### 2.9. Convex Optimization Algorithm

#### 2.10. Real-Time Energy Management Strategy (R-EMS)

_{f}, d]. Finally, d is provided to the converter as an update value for the duty cycle to change the output voltage according to the load demand. Meanwhile, the field current will be fed to the alternator to change the output voltage. Similar to the above work, the authors [28] designed an experimental setup circuit that used the multi-variable sliding mode ESC algorithm. Instead of using one PWM (Pulse Width Modulation) for the boost converter, the author added another PWM controller to the field circuit regulator of the alternator as a buck converter. The schematic diagram for the proposed circuit is illustrated in Figure 29.

## 3. Optimization Using Power Electronic Techniques

## 4. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Block diagram for the experimental test rig [13].

**Figure 2.**Block diagram of PMP control algorithm [13].

**Figure 3.**Result for state of charge of the battery using the proposed algorithm [13].

**Figure 4.**Battery and alternator current for the PMP and EVR algorithms [13].

**Figure 5.**Battery and alternator current for the PMP and EVR algorithms [13].

**Figure 6.**Flowchart for adaptive PMP algorithm [13].

**Figure 7.**Modes of operation for the intelligent alternator [14].

**Figure 8.**Flowchart for the OPD optimization algorithm [14].

**Figure 9.**Experimental results for the proposed algorithm (

**a**) alternator voltage, (

**b**) battery SOC, and (

**c**) alternator, load, and battery power [14].

**Figure 10.**PID controller for alternator voltage regulator [15].

**Figure 11.**Simulation results for the proposed algorithm [15].

**Figure 12.**Energy management controller for the vehicle “Reprinted from [16]”.

**Figure 13.**MPC block diagram for the BSA “Reprinted from [17]”.

**Figure 14.**Transfer function block diagram of the proposed system “Adapted with permission from [18]”.

**Figure 15.**Step response for the per-unit output voltage variation under different variation of time constants (

**a**) τ

_{A}(

**b**) τ

_{E}(

**c**) τ

_{G}(

**d**) τ

_{S}“Adapted with permission from Ref. [18]”.

**Figure 16.**Transfer function block diagram of the proposed system [19].

**Figure 17.**Experimental results using ELP, (

**a**) output voltage of the alternator, (

**b**) SOC of the battery, and (

**c**) change in power contrast [19].

**Figure 18.**Algorithm for the proposed optimization approach “Reprinted from Ref. [20]”.

**Figure 19.**Simulink model for the proposed optimization algorithm [21].

**Figure 20.**Simulation result for the SOC, engine power (P

_{ice}), and battery-motor system power (P

_{ess}) at different speeds values (ν) [21].

**Figure 21.**Control structure of power system for the vehicle [23].

**Figure 22.**Simulation results for the SOC and fuel consumption (E

_{eq}) using the proposed algorithm [23].

**Figure 23.**Case study one for the proposed optimizer [24].

**Figure 24.**Case study two for the proposed optimizer [24].

**Figure 25.**Proposed hybrid optimization circuit “Reprinted from [25]”.

**Figure 26.**Proposed multi-surface sliding mode ESC block diagram “Adapted with permission from Ref. [26]”.

**Figure 27.**Step response for the alternator when applying the multi-surface algorithm “Adapted from [26]”.

**Figure 28.**Proposed multivariable sliding mode ESC “Adapted with permission from [27]”.

**Figure 29.**Block diagram for the proposed control circuit “Adapted with permission from [28]”.

**Figure 30.**Experimental setup for the real-time circuit “Reprinted and adapted with permission from [28]”.

**Figure 31.**Output power for the converter “Adapted with permission from [28]”.

**Figure 32.**Closed-loop test for the PM alternator with switched-mode regulator (SMR) [29].

**Figure 33.**Output power for PM alternator with switched-mode regulator (SMR) “Adapted with permission from [32]”.

**Figure 34.**Induction generator with inverter and bridge rectifier [36].

**Figure 35.**Variable frequency SCR controller block diagram “Reprinted from [37]”.

**Figure 36.**AFPM connection for the engine and inverter block diagram [38].

**Figure 37.**Controllers for the proposed system “Reprinted from [42]”.

**Figure 38.**Matlab Simulink setup for the alternator, rectifier, and controller “Reprinted from [47]”.

**Figure 39.**Experimental setup for the controller and alternator/rectifier “Reprinted from [47]”.

**Figure 40.**New dual output SMR circuit diagram “Reprinted from [48]”.

**Figure 41.**Alternative circuit diagram for the SMRs “Reprinted from [48]”.

**Figure 42.**The schematic diagram for the direct frequency tracing “Reprinted from [49]”.

**Figure 43.**Flowchart for the D-FT algorithm “Reprinted from [49]”.

Item No. | Year | Status |
---|---|---|

1 | Before the 1960s | Only the ignition was the primary load for the battery and the alternator. |

2 | After the 1960s | The power requirement of upper-class automobiles has climbed from less than 500 W. |

3 | In the 2000 year | More than 2 kW and will continue to rise. |

4 | In the coming decade | An accelerated growth to around 10 kW. |

Researchers | Algorithm | Enhancement | Disadvantages |
---|---|---|---|

Waldman et al., 2015, [13] | PMP and global, optimum controller | 2.1% reduction in fuel. Small voltage and current fluctuation enhanced the battery lifetime. | Limited field current range and did not deal with the output voltage control. The output voltage has more ripple content as compared with EVR technology. It is not applied in the real world; it is only used in ECU software. The alternator type is not specified in this work. |

Wang et al., 2016, [14] | OPD | Real-time appropriate strategy. 1.7% fuel reduction. It is applied in real life to passenger vehicles (designed by Hella (Lippstadt)), and the Bosch alternator is used in this work. | Complex approach needing complex calculations. The alternator type is not specified in this work, the work is only a simulation, and it is not applied in the real world. |

Couch, Fiorentini, and Canova, 2013, [15] | ECMS | Ensures a current harmony between the alternator, load, and battery currents and reduces the fuel in average percentages of 1.5% and 25%, respectively. | The action is limited to the field current variation, and the ECMS leads to a 100 to 300% increase in the overall battery consumption, which may influence durability. The type of the alternator is not specified, and this strategy is not applied in the real world. |

Koot et al., 2005, [16] | Modified DP | Reduction in fuel use of 2%, significant emissions reductions. It can be applied quickly and smoothly. | No experimental work is achieved to verify the results for the proposed algorithm. The type of the alternator is not specified (only the general term for integrated starter/alternator), and this strategy is not applied in the real world. |

Han et al., 2017, [17] | MPC | Smooth and fast starting time for the alternator-based engine (0.3 s). The results demonstrate that the engine can start rapidly with minimal speed oscillations. | No experimental work is achieved to verify the results for the proposed algorithm, it is only a comparison between Matlab and AMESim software, and it is not applied in the real world. The type of the alternator is not specified. Only a general belt starter/alternator term is used. |

Chatterjee and Mukherjee, 2016, [18] | TLBO | Good voltage response can be implemented online. Simulation results demonstrate that the TLBO-based PID controller is a vital AVR optimization tool. | It only controls the field current of the alternator. No practical work is introduced in this paper, and also the alternator type is not specified. |

Wang et al., 2018, [19] | DCR and ELP | Stable load power and 1.6% reduction in fuel. The experimental result is obtained depending on real vehicles and alternator parameters. | Fluctuation of battery SOC and high computational complexity. The alternator type is not mentioned in work (only the term intelligent alternator). |

Winter, Taube, and Herzog, 2018, [20] | Multi-Objective | Select the desired system behavior and discover high-effect parameters. | Simulation work only. Alternator type is not mentioned in the work, and the work is not applied in the real world car. |

Xia, Du, and Zhang, 2017, [21] | Quadratic optimization | The optimization index deals with the battery SOC and fuel reduction simultaneously. Fuel consumption is reduced by 3.7%. Toyota Prius parameters are used as a vehicle in this work. | Simulation work only, two motor-generator set is used, and it needs extra components and cost. Alternator type is not mentioned in this work. |

Marinkov, Murgovski, and Jager, 2017, [22] | Convex Optimization | Price is reduced by about 8.1%, Can implement online. Only a real-world driving cycle is used. | It is only simulation work, numerical analysis, and lowers fuel reduction. The alternator type is not mentioned in this work. |

Wu et al., 2019, [23] | R-EMS | Significant effect on the SOC for the battery and fuel consumption for the engine. Real-time driving cycles are used. | These devices have low efficiency, less than 50%, and the alternator has a high output at the idle speed, but it is down at high rates. The alternator type is not specified. |

Fan, 2011, [24] | MDO | Reduced size for the system components, fast response. As indicated by the GM Impala, the Parameters of Denso are used in this work as a real word alternator. | It needs extra components; finally, the work is only a simulation, not a real-time one. |

Lins Rodrigues, Cunha Oliveira, and Nogueira Lima, 2019, [25] | Model-based Extremum Seeking | Real-time applicable hybrid optimization, fast, high accuracy, and good enhancement in power in 6–7%. An automotive Lundell alternator is used in this work. | Simulation work only. |

Toloue and Moallem, 2015, [26] | Sliding mode multi-surface | High efficiency, smooth, fast, and robust performance. In addition, this method has less fluctuation, increasing the precision for speed performance. Parameters of the Lundell alternator are used in this work. | Simulation works only and has high computational complexity. |

Tolue and Moallem 2016, [27] | Multivariable Sliding-mode Extremum Seeking | Fast and precise convergence and robust performance in the face of disturbances and uncertainties. The parameters of the Lundell alternator are used. | Simulation work only. |

Tolue and Moallem 2017, [28] | Experimental MVESC (Multivariable Sliding-mode Extremum Seeking) | Advantages in robust performance, speed, and accuracy. The system is used in the real-world railway industry. The alternator type is remanufactured ACDelco 334-2224A | Compacted system and expensive. It needs ADC and DAC and tow choppers. |

Researchers | Algorithm | Enhancement | Disadvantages |
---|---|---|---|

C.-Z. Liaw, 2013, [29] | SMR | Improved the output power by 66%, high efficiency is obtained at low speeds, and finally, acceptable voltage fluctuation is measured. The type of the alternator is interior PM. This work is experimental. | No investigation has been made for the alternator performance at higher speeds. The accuracy of the proposed system is affected by the rectifier’s presence. |

Henry et al., 2001, [35] | Inverter and DC/DC converter | The net efficiency was in the range of (73–79%). | The complex controller provides an output power of about 4 kW, but at high speed, this power was reduced to half at 4000 rpm, for example. |

Naidu and Walters, 2003, [36] | Diode rectifier and voltage source PWM inverter | High efficacy at low speeds, but an excellent transient response for the controller was optioned. An induction generator is used as the power source in this work | It has lower efficiency at full speed, needing a complex controller. Not applied in the real world, and the work is a simulation only. |

Naidu, Henry, and Boules, 2000, [37] | SCR rectifier | The obtained power was high at full speed, and the efficiency was 71%. A real-world Delphi R&D PM alternator is used in this work. | It used a complex controller. |

El-Hasan, 2018, [38] | Full controlled AC to DC convertor | High efficiency is optioned (94%) and good voltage regulation. Axial-flux PM(AFPM) S/A alternator is used in a real LGA 340 OHC Lombardini engine. | The system suffered from temperature rise when the load was 49 A. |

Liang, Miller, and Zarei, 1996, [40] | Six-step inverter | Output increased by 43%, and a good response was obtained. The salient pole Lundell alternator is the alternator type used in this work. | The system suffers from a high fluctuating of the output voltage. Experimental work is present but not used in the real world. |

Perreault and Caliskan, 2004, [42] | Half-bridge SMR | They increase the output power linearly from 1 kW at idle speed (1800 rpm) to about 4 kW (6000 rpm). Lundell alternator is used in this work. | The system has low energy and efficiency at low speeds. |

Hassan, Perreault, and Keim, 2005, [48] | Dual output SMR | Results indicated a good response and performance for the proposed combination. Slandered Lundell alternator (14-V 65/130 A) is used in this work. It is used as an experimental setup to verify the proposed system. | Complex circuit, and it needs an axillary control device. It works only on the alternator’s output, not on the regulating of the field current. |

J. Wan, 2022, [49] | D-FTSR | A novel approach to tracking the engine speed to control the alternator output frequency enhanced alternator efficiency by 8% and can be applicable in a wide range of alternators. The work is verified using an experimental setup. | It controls only the rectifier output and does not deal with the field voltage control. The type of the alternator is not specified in this work. |

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## Share and Cite

**MDPI and ACS Style**

Mahmood, O.T.; Wan Hasan, W.Z.; Ismail, L.I.; Shafie, S.; Azis, N.; Norsahperi, N.M.H.
Optimization Approaches and Techniques for Automotive Alternators: Review Study. *Machines* **2022**, *10*, 478.
https://doi.org/10.3390/machines10060478

**AMA Style**

Mahmood OT, Wan Hasan WZ, Ismail LI, Shafie S, Azis N, Norsahperi NMH.
Optimization Approaches and Techniques for Automotive Alternators: Review Study. *Machines*. 2022; 10(6):478.
https://doi.org/10.3390/machines10060478

**Chicago/Turabian Style**

Mahmood, Omar Talal, Wan Zuha Wan Hasan, Luthffi Idzhar Ismail, Suhaidi Shafie, Norhafiz Azis, and Nor Mohd Haziq Norsahperi.
2022. "Optimization Approaches and Techniques for Automotive Alternators: Review Study" *Machines* 10, no. 6: 478.
https://doi.org/10.3390/machines10060478