# Drivability Optimization of Electric Vehicle Drivetrains for Brake Blending Maneuvers

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## Abstract

**:**

## 1. Introduction and Motivation

## 2. Test Environment

## 3. Drivability Function

## 4. Dynamics of the Braking System

## 5. Regenerative Braking System

## 6. Conventional Vehicle Braking System

## 7. Brake Blending

## 8. Summary and Outlook

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**Torque–angular velocity characteristic for drive machines in regeneration mode according to [5].

**Figure 2.**Regenerative braking and brake blending according to [1].

**Figure 5.**Positions of the relevant sensors of the applied HiL test bench and the relevant, corresponding measured values.

**Figure 8.**Emulation of a CAN bus network for the signal of the angular velocity of the vehicle wheel hub.

**Figure 9.**Pressure build-up dynamics in the vehicle wheel brake of the HiL test bench in the event of a step in the desired pressure.

**Figure 10.**Regenerative braking operation from 25 km/h with activated prefilter and deactivated anti-jerk control.

**Figure 11.**Regenerative braking operation from 25 km/h with activated prefilter and anti-jerk control.

**Figure 12.**Braking operation with a conventional vehicle braking system from 25 km/h with deactivated anti-jerk control.

**Figure 13.**Braking operation with a conventional vehicle braking system from 25 km/h with activated anti-jerk control.

**Figure 14.**Braking operation with fixed 50/50 split between the drive machine and the conventional vehicle braking system from 25 km/h with activated prefilter and deactivated anti-jerk control.

**Figure 15.**Braking operation with fixed 50/50 split between the drive machine and the conventional vehicle braking system from 25 km/h with activated prefilter and anti-jerk control.

**Figure 16.**Braking operation with a variable split between the drive machine and the conventional vehicle braking system from 25 km/h with activated prefilter and anti-jerk control.

Braking Operation | $\mathbf{Time}{\mathit{t}}_{63}\mathbf{until}63\%\mathbf{of}\mathbf{the}\mathbf{Total}\mathbf{Desired}\mathbf{Braking}\mathbf{Torque}\mathbf{Is}\mathbf{Reached}\left(\mathbf{ms}\right)$ | $\mathbf{Time}{\mathit{t}}_{90}\mathbf{until}90\%\mathbf{of}\mathbf{the}\mathbf{Total}\mathbf{Desired}\mathbf{Braking}\mathbf{Torque}\mathbf{Is}\mathbf{Reached}\left(\mathbf{ms}\right)$ |
---|---|---|

Regenerative braking system without AJC | 54 | 77 |

Regenerative braking system with AJC | 57 | 85 |

Conventional braking system without AJC | 59 | 105 |

Conventional braking system with AJC | 60 | 102 |

Brake blending without AJC | 56 | 87 |

Brake blending with AJC | 59 | 91 |

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**MDPI and ACS Style**

Koch, A.; Brauer, J.; Falkenstein, J.
Drivability Optimization of Electric Vehicle Drivetrains for Brake Blending Maneuvers. *World Electr. Veh. J.* **2022**, *13*, 209.
https://doi.org/10.3390/wevj13110209

**AMA Style**

Koch A, Brauer J, Falkenstein J.
Drivability Optimization of Electric Vehicle Drivetrains for Brake Blending Maneuvers. *World Electric Vehicle Journal*. 2022; 13(11):209.
https://doi.org/10.3390/wevj13110209

**Chicago/Turabian Style**

Koch, Andreas, Jonas Brauer, and Jens Falkenstein.
2022. "Drivability Optimization of Electric Vehicle Drivetrains for Brake Blending Maneuvers" *World Electric Vehicle Journal* 13, no. 11: 209.
https://doi.org/10.3390/wevj13110209